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- data/vals_ai/Qwen/Qwen2.5-72B-Instruct-Turbo/1228bed5-6603-4226-9ae7-67392111a123.json +491 -0
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data/vals_ai/Qwen/Qwen2.5-72B-Instruct-Turbo/1228bed5-6603-4226-9ae7-67392111a123.json
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| 1 |
+
{
|
| 2 |
+
"schema_version": "0.2.2",
|
| 3 |
+
"evaluation_id": "vals-ai/medqa/Qwen_Qwen2.5-72B-Instruct-Turbo/1782803555.768981",
|
| 4 |
+
"retrieved_timestamp": "1782803555.768981",
|
| 5 |
+
"source_metadata": {
|
| 6 |
+
"source_name": "Vals.ai Leaderboard - MedQA",
|
| 7 |
+
"source_type": "documentation",
|
| 8 |
+
"source_organization_name": "Vals.ai",
|
| 9 |
+
"source_organization_url": "https://www.vals.ai",
|
| 10 |
+
"evaluator_relationship": "third_party",
|
| 11 |
+
"additional_details": {
|
| 12 |
+
"benchmark_slug": "medqa",
|
| 13 |
+
"benchmark_name": "MedQA",
|
| 14 |
+
"benchmark_updated": "2026-04-16",
|
| 15 |
+
"dataset_type": "public",
|
| 16 |
+
"industry": "healthcare",
|
| 17 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/medqa",
|
| 18 |
+
"extraction_method": "static_astro_benchmark_view_props"
|
| 19 |
+
}
|
| 20 |
+
},
|
| 21 |
+
"eval_library": {
|
| 22 |
+
"name": "Vals.ai",
|
| 23 |
+
"version": "unknown"
|
| 24 |
+
},
|
| 25 |
+
"model_info": {
|
| 26 |
+
"name": "Qwen2.5-72B-Instruct-Turbo",
|
| 27 |
+
"id": "Qwen/Qwen2.5-72B-Instruct-Turbo",
|
| 28 |
+
"developer": "Qwen",
|
| 29 |
+
"additional_details": {
|
| 30 |
+
"vals_model_id": "together/Qwen/Qwen2.5-72B-Instruct-Turbo",
|
| 31 |
+
"vals_provider": "Together AI"
|
| 32 |
+
}
|
| 33 |
+
},
|
| 34 |
+
"evaluation_results": [
|
| 35 |
+
{
|
| 36 |
+
"evaluation_result_id": "medqa:asian:together/Qwen/Qwen2.5-72B-Instruct-Turbo:score",
|
| 37 |
+
"evaluation_name": "vals_ai.medqa.asian",
|
| 38 |
+
"source_data": {
|
| 39 |
+
"dataset_name": "MedQA - Asian",
|
| 40 |
+
"source_type": "url",
|
| 41 |
+
"url": [
|
| 42 |
+
"https://www.vals.ai/benchmarks/medqa"
|
| 43 |
+
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data/vals_ai/Qwen/Qwen2.5-72B-Instruct-Turbo/bbe0ba41-7558-41aa-b811-4e6443348b81.json
ADDED
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@@ -0,0 +1,420 @@
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data/vals_ai/Qwen/Qwen2.5-7B-Instruct-Turbo/e92c17e6-1d7d-48ea-bd3e-4fccdbd54b52.json
ADDED
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@@ -0,0 +1,420 @@
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|
| 1 |
+
{
|
| 2 |
+
"schema_version": "0.2.2",
|
| 3 |
+
"evaluation_id": "vals-ai/legal_bench/Qwen_Qwen2.5-7B-Instruct-Turbo/1782803555.768981",
|
| 4 |
+
"retrieved_timestamp": "1782803555.768981",
|
| 5 |
+
"source_metadata": {
|
| 6 |
+
"source_name": "Vals.ai Leaderboard - LegalBench",
|
| 7 |
+
"source_type": "documentation",
|
| 8 |
+
"source_organization_name": "Vals.ai",
|
| 9 |
+
"source_organization_url": "https://www.vals.ai",
|
| 10 |
+
"evaluator_relationship": "third_party",
|
| 11 |
+
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|
| 12 |
+
"benchmark_slug": "legal_bench",
|
| 13 |
+
"benchmark_name": "LegalBench",
|
| 14 |
+
"benchmark_updated": "2026-06-17",
|
| 15 |
+
"dataset_type": "public",
|
| 16 |
+
"industry": "legal",
|
| 17 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/legal_bench",
|
| 18 |
+
"extraction_method": "static_astro_benchmark_view_props"
|
| 19 |
+
}
|
| 20 |
+
},
|
| 21 |
+
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|
| 22 |
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"name": "Vals.ai",
|
| 23 |
+
"version": "unknown"
|
| 24 |
+
},
|
| 25 |
+
"model_info": {
|
| 26 |
+
"name": "Qwen2.5-7B-Instruct-Turbo",
|
| 27 |
+
"id": "Qwen/Qwen2.5-7B-Instruct-Turbo",
|
| 28 |
+
"developer": "Qwen",
|
| 29 |
+
"additional_details": {
|
| 30 |
+
"vals_model_id": "together/Qwen/Qwen2.5-7B-Instruct-Turbo",
|
| 31 |
+
"vals_provider": "Together AI"
|
| 32 |
+
}
|
| 33 |
+
},
|
| 34 |
+
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|
| 35 |
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{
|
| 36 |
+
"evaluation_result_id": "legal_bench:conclusion_tasks:together/Qwen/Qwen2.5-7B-Instruct-Turbo:score",
|
| 37 |
+
"evaluation_name": "vals_ai.legal_bench.conclusion_tasks",
|
| 38 |
+
"source_data": {
|
| 39 |
+
"dataset_name": "LegalBench - Conclusion Tasks",
|
| 40 |
+
"source_type": "url",
|
| 41 |
+
"url": [
|
| 42 |
+
"https://www.vals.ai/benchmarks/legal_bench"
|
| 43 |
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],
|
| 44 |
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|
| 45 |
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|
| 46 |
+
"task_key": "conclusion_tasks",
|
| 47 |
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|
| 48 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/legal_bench"
|
| 49 |
+
}
|
| 50 |
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|
| 51 |
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|
| 52 |
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"evaluation_description": "Accuracy reported by Vals.ai for LegalBench (Conclusion Tasks).",
|
| 53 |
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|
| 54 |
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|
| 55 |
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|
| 56 |
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|
| 57 |
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|
| 58 |
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|
| 59 |
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|
| 60 |
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|
| 61 |
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|
| 62 |
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| 63 |
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|
| 64 |
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|
| 65 |
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|
| 66 |
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|
| 67 |
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|
| 68 |
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|
| 69 |
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|
| 70 |
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|
| 71 |
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|
| 72 |
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|
| 73 |
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|
| 74 |
+
"task_name": "Conclusion Tasks",
|
| 75 |
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|
| 76 |
+
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|
| 77 |
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|
| 78 |
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|
| 79 |
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|
| 80 |
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|
| 81 |
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|
| 82 |
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|
| 83 |
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|
| 84 |
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|
| 85 |
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|
| 86 |
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|
| 87 |
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|
| 88 |
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|
| 89 |
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|
| 90 |
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|
| 91 |
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|
| 92 |
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|
| 93 |
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| 94 |
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|
| 95 |
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|
| 96 |
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|
| 97 |
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|
| 98 |
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|
| 99 |
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{
|
| 100 |
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"evaluation_result_id": "legal_bench:interpretation_tasks:together/Qwen/Qwen2.5-7B-Instruct-Turbo:score",
|
| 101 |
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|
| 102 |
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|
| 103 |
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"dataset_name": "LegalBench - Interpretation Tasks",
|
| 104 |
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|
| 105 |
+
"url": [
|
| 106 |
+
"https://www.vals.ai/benchmarks/legal_bench"
|
| 107 |
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|
| 108 |
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|
| 109 |
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|
| 110 |
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"task_key": "interpretation_tasks",
|
| 111 |
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"dataset_type": "public",
|
| 112 |
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"leaderboard_page_url": "https://www.vals.ai/benchmarks/legal_bench"
|
| 113 |
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}
|
| 114 |
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|
| 115 |
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|
| 116 |
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"evaluation_description": "Accuracy reported by Vals.ai for LegalBench (Interpretation Tasks).",
|
| 117 |
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|
| 118 |
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|
| 119 |
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|
| 120 |
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|
| 121 |
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|
| 122 |
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|
| 123 |
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|
| 124 |
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|
| 125 |
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|
| 126 |
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|
| 127 |
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|
| 128 |
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|
| 129 |
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|
| 130 |
+
},
|
| 131 |
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|
| 132 |
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|
| 133 |
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"details": {
|
| 134 |
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|
| 135 |
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|
| 136 |
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|
| 137 |
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|
| 138 |
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|
| 139 |
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|
| 140 |
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|
| 141 |
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|
| 142 |
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|
| 143 |
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|
| 144 |
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"temperature": "0.7",
|
| 145 |
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|
| 146 |
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|
| 147 |
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|
| 148 |
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|
| 149 |
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|
| 150 |
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|
| 151 |
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|
| 152 |
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|
| 153 |
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|
| 154 |
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|
| 155 |
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|
| 156 |
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| 157 |
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| 158 |
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|
| 159 |
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|
| 160 |
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|
| 161 |
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|
| 162 |
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|
| 163 |
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|
| 164 |
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"evaluation_result_id": "legal_bench:issue_tasks:together/Qwen/Qwen2.5-7B-Instruct-Turbo:score",
|
| 165 |
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"evaluation_name": "vals_ai.legal_bench.issue_tasks",
|
| 166 |
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"source_data": {
|
| 167 |
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"dataset_name": "LegalBench - Issue Tasks",
|
| 168 |
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|
| 169 |
+
"url": [
|
| 170 |
+
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|
| 171 |
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|
| 172 |
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| 173 |
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|
| 174 |
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|
| 175 |
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|
| 176 |
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|
| 177 |
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| 178 |
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|
| 179 |
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|
| 180 |
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"evaluation_description": "Accuracy reported by Vals.ai for LegalBench (Issue Tasks).",
|
| 181 |
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| 182 |
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|
| 183 |
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|
| 184 |
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|
| 185 |
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|
| 186 |
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|
| 187 |
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| 188 |
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| 189 |
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|
| 190 |
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| 191 |
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|
| 192 |
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|
| 193 |
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|
| 194 |
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|
| 195 |
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|
| 196 |
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|
| 197 |
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| 198 |
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|
| 199 |
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|
| 200 |
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|
| 201 |
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|
| 202 |
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|
| 203 |
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| 204 |
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| 205 |
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| 206 |
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| 207 |
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| 209 |
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| 210 |
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| 211 |
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| 212 |
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| 213 |
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| 214 |
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| 215 |
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|
| 216 |
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| 217 |
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| 218 |
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| 219 |
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| 220 |
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| 221 |
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| 222 |
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| 224 |
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| 226 |
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| 227 |
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|
| 228 |
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| 229 |
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|
| 230 |
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|
| 231 |
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|
| 232 |
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|
| 233 |
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|
| 234 |
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|
| 235 |
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| 236 |
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| 237 |
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| 238 |
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| 239 |
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| 240 |
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| 241 |
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| 242 |
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| 243 |
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|
| 244 |
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| 245 |
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| 246 |
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| 247 |
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| 248 |
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| 249 |
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| 250 |
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| 254 |
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| 256 |
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| 257 |
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|
| 258 |
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|
| 259 |
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|
| 260 |
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|
| 261 |
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|
| 262 |
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|
| 263 |
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|
| 264 |
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|
| 265 |
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|
| 266 |
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|
| 267 |
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|
| 268 |
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|
| 269 |
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|
| 270 |
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|
| 271 |
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|
| 272 |
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|
| 273 |
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| 274 |
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|
| 275 |
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|
| 276 |
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| 277 |
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|
| 279 |
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|
| 280 |
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| 281 |
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| 282 |
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|
| 283 |
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|
| 284 |
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|
| 285 |
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| 286 |
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| 287 |
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|
| 288 |
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|
| 289 |
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|
| 290 |
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|
| 291 |
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{
|
| 292 |
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|
| 293 |
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|
| 294 |
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|
| 295 |
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| 296 |
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|
| 297 |
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|
| 298 |
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|
| 299 |
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|
| 300 |
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| 301 |
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|
| 302 |
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|
| 303 |
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|
| 304 |
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|
| 305 |
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| 306 |
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| 307 |
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| 308 |
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| 309 |
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| 310 |
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| 311 |
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| 312 |
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| 313 |
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| 314 |
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| 315 |
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| 318 |
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| 320 |
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|
| 321 |
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| 322 |
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| 323 |
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| 324 |
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| 325 |
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| 326 |
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| 327 |
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|
| 328 |
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| 329 |
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| 330 |
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| 331 |
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| 332 |
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| 333 |
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| 334 |
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| 339 |
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| 348 |
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| 356 |
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| 358 |
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| 359 |
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| 360 |
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| 361 |
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| 362 |
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| 363 |
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| 364 |
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| 365 |
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| 366 |
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| 384 |
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| 385 |
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|
| 388 |
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|
| 389 |
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|
| 390 |
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| 391 |
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| 392 |
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| 393 |
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| 394 |
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| 395 |
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| 396 |
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| 397 |
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| 398 |
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| 399 |
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| 400 |
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| 401 |
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| 402 |
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| 404 |
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| 405 |
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| 411 |
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|
| 412 |
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| 413 |
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| 414 |
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| 415 |
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|
| 416 |
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|
| 417 |
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|
| 418 |
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|
| 419 |
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|
| 420 |
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data/vals_ai/cursor/composer-2.5/0c990dc9-a21a-46e2-9759-7251f0e275ba.json
ADDED
|
@@ -0,0 +1,96 @@
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|
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|
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|
|
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|
|
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|
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|
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|
|
|
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|
|
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|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
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|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
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|
|
|
|
|
|
|
|
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|
|
|
|
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|
|
|
|
|
|
|
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|
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|
|
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|
|
|
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|
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|
|
|
|
|
|
|
|
|
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|
|
|
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|
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| 1 |
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|
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| 5 |
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| 6 |
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| 7 |
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| 8 |
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|
| 9 |
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|
| 10 |
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| 11 |
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| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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| 16 |
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| 17 |
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| 18 |
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|
| 19 |
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| 20 |
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| 21 |
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| 22 |
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| 23 |
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| 24 |
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| 26 |
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| 27 |
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| 29 |
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| 30 |
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|
| 31 |
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| 32 |
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| 35 |
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| 36 |
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| 37 |
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| 38 |
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| 39 |
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| 40 |
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| 42 |
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| 51 |
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| 52 |
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| 53 |
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| 62 |
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| 63 |
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|
| 65 |
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| 66 |
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|
| 68 |
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| 69 |
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|
| 70 |
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| 71 |
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| 72 |
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|
| 73 |
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| 74 |
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|
| 75 |
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| 76 |
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| 78 |
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| 79 |
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|
| 80 |
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| 81 |
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| 82 |
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| 83 |
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|
| 84 |
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| 85 |
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| 86 |
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|
| 87 |
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|
| 88 |
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|
| 89 |
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| 90 |
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| 91 |
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| 92 |
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| 94 |
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| 95 |
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|
| 96 |
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|
data/vals_ai/cursor/composer-2.5/9b814b26-9c1b-45f3-8fed-4c2a925349f2.json
ADDED
|
@@ -0,0 +1,284 @@
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
|
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|
|
| 1 |
+
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|
| 2 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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|
| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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|
| 20 |
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|
| 21 |
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|
| 22 |
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|
| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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|
| 27 |
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|
| 28 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
| 33 |
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|
| 34 |
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|
| 35 |
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|
| 36 |
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|
| 37 |
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|
| 38 |
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|
| 39 |
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|
| 40 |
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|
| 41 |
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|
| 42 |
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|
| 43 |
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| 44 |
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|
| 45 |
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|
| 46 |
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| 47 |
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|
| 48 |
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| 49 |
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| 50 |
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| 51 |
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|
| 52 |
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| 53 |
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| 54 |
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| 55 |
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| 56 |
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| 58 |
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| 59 |
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| 60 |
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| 62 |
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|
| 64 |
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| 65 |
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| 66 |
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| 67 |
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|
| 68 |
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|
| 69 |
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|
| 70 |
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|
| 71 |
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|
| 72 |
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| 73 |
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|
| 74 |
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|
| 75 |
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|
| 76 |
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|
| 77 |
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|
| 78 |
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|
| 79 |
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| 80 |
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| 81 |
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|
| 82 |
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|
| 83 |
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|
| 84 |
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|
| 85 |
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|
| 86 |
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|
| 87 |
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|
| 88 |
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| 89 |
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|
| 90 |
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|
| 91 |
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|
| 92 |
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|
| 93 |
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|
| 94 |
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|
| 95 |
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|
| 96 |
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|
| 97 |
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|
| 98 |
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|
| 99 |
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| 100 |
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|
| 101 |
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| 102 |
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|
| 103 |
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| 104 |
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| 105 |
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| 106 |
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| 107 |
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|
| 108 |
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| 109 |
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| 110 |
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| 111 |
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| 112 |
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|
| 114 |
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| 115 |
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|
| 116 |
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| 117 |
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|
| 118 |
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| 119 |
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|
| 120 |
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| 121 |
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| 126 |
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| 127 |
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|
| 128 |
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|
| 129 |
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|
| 130 |
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|
| 131 |
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|
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|
| 133 |
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|
| 134 |
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| 135 |
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|
| 136 |
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|
| 137 |
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|
| 138 |
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|
| 139 |
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|
| 140 |
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|
| 141 |
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|
| 142 |
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|
| 143 |
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|
| 144 |
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| 145 |
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|
| 146 |
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| 148 |
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| 149 |
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| 150 |
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| 151 |
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| 152 |
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| 153 |
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| 154 |
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| 155 |
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| 156 |
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|
| 159 |
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|
| 160 |
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|
| 161 |
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|
| 162 |
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|
| 163 |
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|
| 164 |
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| 165 |
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|
| 166 |
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| 167 |
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| 168 |
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|
| 170 |
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| 171 |
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| 172 |
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| 173 |
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| 174 |
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| 175 |
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| 176 |
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| 177 |
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| 178 |
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| 179 |
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| 180 |
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| 188 |
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| 190 |
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| 191 |
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|
| 192 |
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| 193 |
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| 195 |
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| 196 |
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| 197 |
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| 198 |
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| 199 |
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| 200 |
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| 201 |
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| 202 |
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| 204 |
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| 207 |
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| 211 |
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| 214 |
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| 215 |
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| 216 |
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| 217 |
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| 218 |
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| 220 |
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| 221 |
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|
| 222 |
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| 223 |
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| 224 |
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| 225 |
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| 226 |
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| 227 |
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| 228 |
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| 247 |
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| 248 |
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| 250 |
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| 251 |
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| 252 |
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| 253 |
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|
| 254 |
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|
| 255 |
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|
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|
| 257 |
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|
| 258 |
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|
| 259 |
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|
| 260 |
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| 261 |
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|
| 262 |
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|
| 263 |
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|
| 264 |
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|
| 265 |
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|
| 266 |
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|
| 268 |
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|
| 269 |
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|
| 270 |
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|
| 271 |
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|
| 272 |
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|
| 273 |
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| 274 |
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|
| 275 |
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|
| 276 |
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|
| 277 |
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|
| 278 |
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|
| 279 |
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|
| 280 |
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|
| 281 |
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|
| 282 |
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|
| 283 |
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|
| 284 |
+
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|
data/vals_ai/cursor/composer-2.5/ec0da620-ae48-43dd-b83f-208074d5f946.json
ADDED
|
@@ -0,0 +1,346 @@
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| 1 |
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| 2 |
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| 9 |
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| 11 |
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| 14 |
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| 16 |
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| 17 |
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| 18 |
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| 19 |
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| 24 |
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| 25 |
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| 26 |
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| 27 |
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| 28 |
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| 29 |
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| 30 |
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| 31 |
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| 32 |
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| 36 |
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| 37 |
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| 40 |
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| 41 |
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| 42 |
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| 43 |
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| 47 |
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| 48 |
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| 75 |
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| 77 |
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| 87 |
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| 295 |
+
"dataset_type": "public",
|
| 296 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/swebench"
|
| 297 |
+
}
|
| 298 |
+
},
|
| 299 |
+
"metric_config": {
|
| 300 |
+
"evaluation_description": "Accuracy reported by Vals.ai for SWE-bench (Overall).",
|
| 301 |
+
"metric_id": "vals_ai.swebench.overall.accuracy",
|
| 302 |
+
"metric_name": "Accuracy",
|
| 303 |
+
"metric_kind": "accuracy",
|
| 304 |
+
"metric_unit": "percent",
|
| 305 |
+
"lower_is_better": false,
|
| 306 |
+
"score_type": "continuous",
|
| 307 |
+
"min_score": 0.0,
|
| 308 |
+
"max_score": 100.0,
|
| 309 |
+
"additional_details": {
|
| 310 |
+
"score_scale": "percent_0_to_100",
|
| 311 |
+
"max_score_source": "fixed_percentage_bound",
|
| 312 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/swebench"
|
| 313 |
+
}
|
| 314 |
+
},
|
| 315 |
+
"score_details": {
|
| 316 |
+
"score": 79.6,
|
| 317 |
+
"details": {
|
| 318 |
+
"benchmark_slug": "swebench",
|
| 319 |
+
"benchmark_name": "SWE-bench",
|
| 320 |
+
"benchmark_updated": "2026-06-17",
|
| 321 |
+
"task_key": "overall",
|
| 322 |
+
"task_name": "Overall",
|
| 323 |
+
"dataset_type": "public",
|
| 324 |
+
"industry": "coding",
|
| 325 |
+
"raw_score": "79.6",
|
| 326 |
+
"raw_stderr": "1.804",
|
| 327 |
+
"latency": "0",
|
| 328 |
+
"max_output_tokens": "200000",
|
| 329 |
+
"provider": "Cursor"
|
| 330 |
+
},
|
| 331 |
+
"uncertainty": {
|
| 332 |
+
"standard_error": {
|
| 333 |
+
"value": 1.804,
|
| 334 |
+
"method": "vals_reported"
|
| 335 |
+
}
|
| 336 |
+
}
|
| 337 |
+
},
|
| 338 |
+
"generation_config": {
|
| 339 |
+
"generation_args": {
|
| 340 |
+
"max_tokens": 200000,
|
| 341 |
+
"max_attempts": 1
|
| 342 |
+
}
|
| 343 |
+
}
|
| 344 |
+
}
|
| 345 |
+
]
|
| 346 |
+
}
|
data/vals_ai/devin/swe-1-6-fast/06177019-a9ba-46d3-af73-7c6a80172c97.json
ADDED
|
@@ -0,0 +1,89 @@
|
|
|
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|
|
|
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|
|
|
|
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|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"schema_version": "0.2.2",
|
| 3 |
+
"evaluation_id": "vals-ai/vibe-code/devin_swe-1-6-fast/1782803555.768981",
|
| 4 |
+
"retrieved_timestamp": "1782803555.768981",
|
| 5 |
+
"source_metadata": {
|
| 6 |
+
"source_name": "Vals.ai Leaderboard - Vibe Code Bench v1.1",
|
| 7 |
+
"source_type": "documentation",
|
| 8 |
+
"source_organization_name": "Vals.ai",
|
| 9 |
+
"source_organization_url": "https://www.vals.ai",
|
| 10 |
+
"evaluator_relationship": "third_party",
|
| 11 |
+
"additional_details": {
|
| 12 |
+
"benchmark_slug": "vibe-code",
|
| 13 |
+
"benchmark_name": "Vibe Code Bench v1.1",
|
| 14 |
+
"benchmark_updated": "2026-06-17",
|
| 15 |
+
"dataset_type": "private",
|
| 16 |
+
"industry": "coding",
|
| 17 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/vibe-code",
|
| 18 |
+
"extraction_method": "static_astro_benchmark_view_props"
|
| 19 |
+
}
|
| 20 |
+
},
|
| 21 |
+
"eval_library": {
|
| 22 |
+
"name": "Vals.ai",
|
| 23 |
+
"version": "unknown"
|
| 24 |
+
},
|
| 25 |
+
"model_info": {
|
| 26 |
+
"name": "swe-1-6-fast",
|
| 27 |
+
"id": "devin/swe-1-6-fast",
|
| 28 |
+
"developer": "devin",
|
| 29 |
+
"additional_details": {
|
| 30 |
+
"vals_model_id": "devin/swe-1-6-fast",
|
| 31 |
+
"vals_provider": "Devin"
|
| 32 |
+
}
|
| 33 |
+
},
|
| 34 |
+
"evaluation_results": [
|
| 35 |
+
{
|
| 36 |
+
"evaluation_result_id": "vibe-code:overall:devin/swe-1-6-fast:score",
|
| 37 |
+
"evaluation_name": "vals_ai.vibe-code.overall",
|
| 38 |
+
"source_data": {
|
| 39 |
+
"dataset_name": "Vibe Code Bench v1.1 - Overall",
|
| 40 |
+
"source_type": "other",
|
| 41 |
+
"additional_details": {
|
| 42 |
+
"benchmark_slug": "vibe-code",
|
| 43 |
+
"task_key": "overall",
|
| 44 |
+
"dataset_type": "private",
|
| 45 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/vibe-code"
|
| 46 |
+
}
|
| 47 |
+
},
|
| 48 |
+
"metric_config": {
|
| 49 |
+
"evaluation_description": "Accuracy reported by Vals.ai for Vibe Code Bench v1.1 (Overall).",
|
| 50 |
+
"metric_id": "vals_ai.vibe-code.overall.accuracy",
|
| 51 |
+
"metric_name": "Accuracy",
|
| 52 |
+
"metric_kind": "accuracy",
|
| 53 |
+
"metric_unit": "percent",
|
| 54 |
+
"lower_is_better": false,
|
| 55 |
+
"score_type": "continuous",
|
| 56 |
+
"min_score": 0.0,
|
| 57 |
+
"max_score": 100.0,
|
| 58 |
+
"additional_details": {
|
| 59 |
+
"score_scale": "percent_0_to_100",
|
| 60 |
+
"max_score_source": "fixed_percentage_bound",
|
| 61 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/vibe-code"
|
| 62 |
+
}
|
| 63 |
+
},
|
| 64 |
+
"score_details": {
|
| 65 |
+
"score": 7.22,
|
| 66 |
+
"details": {
|
| 67 |
+
"benchmark_slug": "vibe-code",
|
| 68 |
+
"benchmark_name": "Vibe Code Bench v1.1",
|
| 69 |
+
"benchmark_updated": "2026-06-17",
|
| 70 |
+
"task_key": "overall",
|
| 71 |
+
"task_name": "Overall",
|
| 72 |
+
"dataset_type": "private",
|
| 73 |
+
"industry": "coding",
|
| 74 |
+
"raw_score": "7.22",
|
| 75 |
+
"raw_stderr": "2.635",
|
| 76 |
+
"latency": "189.132",
|
| 77 |
+
"max_output_tokens": "0",
|
| 78 |
+
"provider": "Devin"
|
| 79 |
+
},
|
| 80 |
+
"uncertainty": {
|
| 81 |
+
"standard_error": {
|
| 82 |
+
"value": 2.635,
|
| 83 |
+
"method": "vals_reported"
|
| 84 |
+
}
|
| 85 |
+
}
|
| 86 |
+
}
|
| 87 |
+
}
|
| 88 |
+
]
|
| 89 |
+
}
|
data/vals_ai/google/gemini-1.0-pro-002/dcdcf7e4-a2e8-4e91-97b4-595d6ddf4cb6.json
ADDED
|
@@ -0,0 +1,408 @@
|
|
|
|
|
|
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|
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|
|
|
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|
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|
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|
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|
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|
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|
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|
|
|
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|
|
|
| 1 |
+
{
|
| 2 |
+
"schema_version": "0.2.2",
|
| 3 |
+
"evaluation_id": "vals-ai/legal_bench/google_gemini-1.0-pro-002/1782803555.768981",
|
| 4 |
+
"retrieved_timestamp": "1782803555.768981",
|
| 5 |
+
"source_metadata": {
|
| 6 |
+
"source_name": "Vals.ai Leaderboard - LegalBench",
|
| 7 |
+
"source_type": "documentation",
|
| 8 |
+
"source_organization_name": "Vals.ai",
|
| 9 |
+
"source_organization_url": "https://www.vals.ai",
|
| 10 |
+
"evaluator_relationship": "third_party",
|
| 11 |
+
"additional_details": {
|
| 12 |
+
"benchmark_slug": "legal_bench",
|
| 13 |
+
"benchmark_name": "LegalBench",
|
| 14 |
+
"benchmark_updated": "2026-06-17",
|
| 15 |
+
"dataset_type": "public",
|
| 16 |
+
"industry": "legal",
|
| 17 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/legal_bench",
|
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data/vals_ai/google/gemini-1.5-flash-001/f3f8b998-89e7-41a7-a284-b83544188b6a.json
ADDED
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@@ -0,0 +1,276 @@
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| 237 |
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"max_score": 100.0,
|
| 238 |
+
"additional_details": {
|
| 239 |
+
"score_scale": "percent_0_to_100",
|
| 240 |
+
"max_score_source": "fixed_percentage_bound",
|
| 241 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/corp_fin_v2"
|
| 242 |
+
}
|
| 243 |
+
},
|
| 244 |
+
"score_details": {
|
| 245 |
+
"score": 21.445,
|
| 246 |
+
"details": {
|
| 247 |
+
"benchmark_slug": "corp_fin_v2",
|
| 248 |
+
"benchmark_name": "CorpFin v2",
|
| 249 |
+
"benchmark_updated": "2026-06-17",
|
| 250 |
+
"task_key": "shared_max_context",
|
| 251 |
+
"task_name": "Shared Max Context",
|
| 252 |
+
"dataset_type": "private",
|
| 253 |
+
"industry": "finance",
|
| 254 |
+
"raw_score": "21.445",
|
| 255 |
+
"raw_stderr": "1.401",
|
| 256 |
+
"latency": "0.059",
|
| 257 |
+
"cost_per_test": "0.005006",
|
| 258 |
+
"max_output_tokens": "8192",
|
| 259 |
+
"provider": "Google"
|
| 260 |
+
},
|
| 261 |
+
"uncertainty": {
|
| 262 |
+
"standard_error": {
|
| 263 |
+
"value": 1.401,
|
| 264 |
+
"method": "vals_reported"
|
| 265 |
+
}
|
| 266 |
+
}
|
| 267 |
+
},
|
| 268 |
+
"generation_config": {
|
| 269 |
+
"generation_args": {
|
| 270 |
+
"max_tokens": 8192,
|
| 271 |
+
"max_attempts": 1
|
| 272 |
+
}
|
| 273 |
+
}
|
| 274 |
+
}
|
| 275 |
+
]
|
| 276 |
+
}
|
data/vals_ai/google/gemini-1.5-flash-002/03b06b69-5f43-40ea-9cd2-21a044e0ca86.json
ADDED
|
@@ -0,0 +1,981 @@
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data/vals_ai/google/gemini-1.5-flash-002/15f5e37d-a115-4d47-ad22-5d511fd7cff7.json
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@@ -0,0 +1,225 @@
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|
| 1 |
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| 2 |
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| 26 |
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| 27 |
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| 197 |
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| 199 |
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| 200 |
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| 201 |
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| 202 |
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| 203 |
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| 204 |
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| 214 |
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| 217 |
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| 218 |
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|
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|
data/vals_ai/google/gemini-1.5-flash-002/2850f115-e5ce-42ce-a5bf-8bcaf55a091a.json
ADDED
|
@@ -0,0 +1,216 @@
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|
|
|
|
|
|
| 1 |
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{
|
| 2 |
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|
| 3 |
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| 4 |
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| 5 |
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data/vals_ai/google/gemini-1.5-flash-002/4ee05046-cf52-4301-a477-282ede77be12.json
ADDED
|
@@ -0,0 +1,204 @@
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data/vals_ai/google/gemini-1.5-flash-002/6672691c-ff0e-409f-a8b4-ef6ac0316ce9.json
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data/vals_ai/google/gemini-1.5-flash-002/7e409542-e6e4-4bd0-87bc-2fbfe8e1f846.json
ADDED
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@@ -0,0 +1,408 @@
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data/vals_ai/google/gemini-1.5-flash-002/84088ee9-a4a6-4cf2-8d1d-4711ab9ed15a.json
ADDED
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@@ -0,0 +1,792 @@
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|
|
| 1 |
+
{
|
| 2 |
+
"schema_version": "0.2.2",
|
| 3 |
+
"evaluation_id": "vals-ai/mgsm/google_gemini-1.5-flash-002/1782803555.768981",
|
| 4 |
+
"retrieved_timestamp": "1782803555.768981",
|
| 5 |
+
"source_metadata": {
|
| 6 |
+
"source_name": "Vals.ai Leaderboard - MGSM",
|
| 7 |
+
"source_type": "documentation",
|
| 8 |
+
"source_organization_name": "Vals.ai",
|
| 9 |
+
"source_organization_url": "https://www.vals.ai",
|
| 10 |
+
"evaluator_relationship": "third_party",
|
| 11 |
+
"additional_details": {
|
| 12 |
+
"benchmark_slug": "mgsm",
|
| 13 |
+
"benchmark_name": "MGSM",
|
| 14 |
+
"benchmark_updated": "2026-01-09",
|
| 15 |
+
"dataset_type": "public",
|
| 16 |
+
"industry": "math",
|
| 17 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/mgsm",
|
| 18 |
+
"extraction_method": "static_astro_benchmark_view_props"
|
| 19 |
+
}
|
| 20 |
+
},
|
| 21 |
+
"eval_library": {
|
| 22 |
+
"name": "Vals.ai",
|
| 23 |
+
"version": "unknown"
|
| 24 |
+
},
|
| 25 |
+
"model_info": {
|
| 26 |
+
"name": "gemini-1.5-flash-002",
|
| 27 |
+
"id": "google/gemini-1.5-flash-002",
|
| 28 |
+
"developer": "google",
|
| 29 |
+
"additional_details": {
|
| 30 |
+
"vals_model_id": "google/gemini-1.5-flash-002",
|
| 31 |
+
"vals_provider": "Google"
|
| 32 |
+
}
|
| 33 |
+
},
|
| 34 |
+
"evaluation_results": [
|
| 35 |
+
{
|
| 36 |
+
"evaluation_result_id": "mgsm:mgsm_bn:google/gemini-1.5-flash-002:score",
|
| 37 |
+
"evaluation_name": "vals_ai.mgsm.mgsm_bn",
|
| 38 |
+
"source_data": {
|
| 39 |
+
"dataset_name": "MGSM - Bengali",
|
| 40 |
+
"source_type": "url",
|
| 41 |
+
"url": [
|
| 42 |
+
"https://www.vals.ai/benchmarks/mgsm"
|
| 43 |
+
],
|
| 44 |
+
"additional_details": {
|
| 45 |
+
"benchmark_slug": "mgsm",
|
| 46 |
+
"task_key": "mgsm_bn",
|
| 47 |
+
"dataset_type": "public",
|
| 48 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/mgsm"
|
| 49 |
+
}
|
| 50 |
+
},
|
| 51 |
+
"metric_config": {
|
| 52 |
+
"evaluation_description": "Accuracy reported by Vals.ai for MGSM (Bengali).",
|
| 53 |
+
"metric_id": "vals_ai.mgsm.mgsm_bn.accuracy",
|
| 54 |
+
"metric_name": "Accuracy",
|
| 55 |
+
"metric_kind": "accuracy",
|
| 56 |
+
"metric_unit": "percent",
|
| 57 |
+
"lower_is_better": false,
|
| 58 |
+
"score_type": "continuous",
|
| 59 |
+
"min_score": 0.0,
|
| 60 |
+
"max_score": 100.0,
|
| 61 |
+
"additional_details": {
|
| 62 |
+
"score_scale": "percent_0_to_100",
|
| 63 |
+
"max_score_source": "fixed_percentage_bound",
|
| 64 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/mgsm"
|
| 65 |
+
}
|
| 66 |
+
},
|
| 67 |
+
"score_details": {
|
| 68 |
+
"score": 85.6,
|
| 69 |
+
"details": {
|
| 70 |
+
"benchmark_slug": "mgsm",
|
| 71 |
+
"benchmark_name": "MGSM",
|
| 72 |
+
"benchmark_updated": "2026-01-09",
|
| 73 |
+
"task_key": "mgsm_bn",
|
| 74 |
+
"task_name": "Bengali",
|
| 75 |
+
"dataset_type": "public",
|
| 76 |
+
"industry": "math",
|
| 77 |
+
"raw_score": "85.6",
|
| 78 |
+
"raw_stderr": "2.22",
|
| 79 |
+
"latency": "1.932",
|
| 80 |
+
"cost_per_test": "9.5e-05",
|
| 81 |
+
"max_output_tokens": "8192",
|
| 82 |
+
"provider": "Google"
|
| 83 |
+
},
|
| 84 |
+
"uncertainty": {
|
| 85 |
+
"standard_error": {
|
| 86 |
+
"value": 2.22,
|
| 87 |
+
"method": "vals_reported"
|
| 88 |
+
}
|
| 89 |
+
}
|
| 90 |
+
},
|
| 91 |
+
"generation_config": {
|
| 92 |
+
"generation_args": {
|
| 93 |
+
"max_tokens": 8192,
|
| 94 |
+
"max_attempts": 1
|
| 95 |
+
}
|
| 96 |
+
}
|
| 97 |
+
},
|
| 98 |
+
{
|
| 99 |
+
"evaluation_result_id": "mgsm:mgsm_de:google/gemini-1.5-flash-002:score",
|
| 100 |
+
"evaluation_name": "vals_ai.mgsm.mgsm_de",
|
| 101 |
+
"source_data": {
|
| 102 |
+
"dataset_name": "MGSM - German",
|
| 103 |
+
"source_type": "url",
|
| 104 |
+
"url": [
|
| 105 |
+
"https://www.vals.ai/benchmarks/mgsm"
|
| 106 |
+
],
|
| 107 |
+
"additional_details": {
|
| 108 |
+
"benchmark_slug": "mgsm",
|
| 109 |
+
"task_key": "mgsm_de",
|
| 110 |
+
"dataset_type": "public",
|
| 111 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/mgsm"
|
| 112 |
+
}
|
| 113 |
+
},
|
| 114 |
+
"metric_config": {
|
| 115 |
+
"evaluation_description": "Accuracy reported by Vals.ai for MGSM (German).",
|
| 116 |
+
"metric_id": "vals_ai.mgsm.mgsm_de.accuracy",
|
| 117 |
+
"metric_name": "Accuracy",
|
| 118 |
+
"metric_kind": "accuracy",
|
| 119 |
+
"metric_unit": "percent",
|
| 120 |
+
"lower_is_better": false,
|
| 121 |
+
"score_type": "continuous",
|
| 122 |
+
"min_score": 0.0,
|
| 123 |
+
"max_score": 100.0,
|
| 124 |
+
"additional_details": {
|
| 125 |
+
"score_scale": "percent_0_to_100",
|
| 126 |
+
"max_score_source": "fixed_percentage_bound",
|
| 127 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/mgsm"
|
| 128 |
+
}
|
| 129 |
+
},
|
| 130 |
+
"score_details": {
|
| 131 |
+
"score": 88.4,
|
| 132 |
+
"details": {
|
| 133 |
+
"benchmark_slug": "mgsm",
|
| 134 |
+
"benchmark_name": "MGSM",
|
| 135 |
+
"benchmark_updated": "2026-01-09",
|
| 136 |
+
"task_key": "mgsm_de",
|
| 137 |
+
"task_name": "German",
|
| 138 |
+
"dataset_type": "public",
|
| 139 |
+
"industry": "math",
|
| 140 |
+
"raw_score": "88.4",
|
| 141 |
+
"raw_stderr": "2.025",
|
| 142 |
+
"latency": "1.511",
|
| 143 |
+
"cost_per_test": "6.5e-05",
|
| 144 |
+
"max_output_tokens": "8192",
|
| 145 |
+
"provider": "Google"
|
| 146 |
+
},
|
| 147 |
+
"uncertainty": {
|
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data/vals_ai/google/gemini-1.5-flash-002/8f75c4eb-0ceb-438e-89e2-fbac1d1b0424.json
ADDED
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@@ -0,0 +1,288 @@
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| 264 |
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| 265 |
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| 267 |
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| 268 |
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|
| 270 |
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| 277 |
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| 280 |
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| 281 |
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| 284 |
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| 285 |
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| 286 |
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|
| 287 |
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|
| 288 |
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|
data/vals_ai/google/gemini-1.5-flash-002/b4d5c708-7af5-437d-ab02-451fef628983.json
ADDED
|
@@ -0,0 +1,99 @@
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
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|
|
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|
|
|
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|
|
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|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
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|
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|
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|
|
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|
|
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|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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|
| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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| 16 |
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|
| 18 |
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|
| 19 |
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|
| 20 |
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| 21 |
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|
| 22 |
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|
| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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|
| 27 |
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| 28 |
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|
| 29 |
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|
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|
| 31 |
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| 184 |
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|
| 185 |
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|
| 186 |
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|
| 187 |
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|
| 188 |
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|
| 189 |
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|
| 190 |
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|
| 191 |
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| 192 |
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|
| 193 |
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|
| 194 |
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|
| 195 |
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| 196 |
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|
| 197 |
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|
| 198 |
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| 199 |
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|
| 200 |
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| 201 |
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| 202 |
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| 203 |
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| 204 |
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| 205 |
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| 206 |
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| 207 |
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| 208 |
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|
| 209 |
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|
| 210 |
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|
| 211 |
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|
| 212 |
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|
| 213 |
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|
| 214 |
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|
| 215 |
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|
| 216 |
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|
| 217 |
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|
| 218 |
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|
| 219 |
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|
| 220 |
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|
| 221 |
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|
| 222 |
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|
| 223 |
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|
| 224 |
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|
| 225 |
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| 226 |
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|
| 229 |
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| 230 |
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| 231 |
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|
| 232 |
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|
| 233 |
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|
| 234 |
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|
| 235 |
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|
| 236 |
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|
| 237 |
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|
| 238 |
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|
| 239 |
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|
| 240 |
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|
| 241 |
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|
| 242 |
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|
| 243 |
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|
| 244 |
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|
| 245 |
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|
| 246 |
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|
| 247 |
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|
| 248 |
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|
| 249 |
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|
| 250 |
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|
| 251 |
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|
| 252 |
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|
| 253 |
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|
| 254 |
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|
| 255 |
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|
| 256 |
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|
| 257 |
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|
| 258 |
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|
| 259 |
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|
| 260 |
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|
| 261 |
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|
| 262 |
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|
| 263 |
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|
| 264 |
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|
| 265 |
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|
| 266 |
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|
| 267 |
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|
| 268 |
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|
| 269 |
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|
| 270 |
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|
| 271 |
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|
| 272 |
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|
| 273 |
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|
| 274 |
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|
| 275 |
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|
| 276 |
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|
data/vals_ai/google/gemini-1.5-flash-002/bbf2e577-cbd3-4231-919f-6fdfc402b4a4.json
ADDED
|
@@ -0,0 +1,99 @@
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|
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|
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|
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|
|
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|
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|
|
|
|
|
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|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
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| 2 |
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| 3 |
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| 4 |
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| 5 |
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| 6 |
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| 7 |
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| 8 |
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| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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|
| 13 |
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| 14 |
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|
| 15 |
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| 16 |
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| 17 |
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| 18 |
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|
| 19 |
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| 20 |
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| 21 |
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|
| 22 |
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|
| 23 |
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| 24 |
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| 25 |
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| 26 |
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|
| 27 |
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| 28 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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| 32 |
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| 33 |
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|
| 34 |
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|
| 35 |
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|
| 36 |
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| 37 |
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| 39 |
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| 40 |
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| 41 |
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|
| 42 |
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| 43 |
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| 44 |
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| 45 |
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| 47 |
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| 48 |
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| 52 |
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| 57 |
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| 64 |
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| 65 |
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| 67 |
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|
| 68 |
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|
| 69 |
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|
| 70 |
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|
| 71 |
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|
| 72 |
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|
| 73 |
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|
| 74 |
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|
| 75 |
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| 76 |
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| 77 |
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| 78 |
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|
| 79 |
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| 80 |
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| 81 |
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| 82 |
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|
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| 88 |
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| 89 |
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| 90 |
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| 91 |
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| 92 |
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| 93 |
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| 95 |
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| 97 |
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| 98 |
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|
| 99 |
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|
data/vals_ai/google/gemini-1.5-pro-002/275a02e0-dccc-422d-8069-d6a521becf92.json
ADDED
|
@@ -0,0 +1,225 @@
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|
|
|
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|
|
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|
|
|
|
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|
| 1 |
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|
| 2 |
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|
| 3 |
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| 4 |
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| 5 |
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|
| 6 |
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|
| 7 |
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|
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|
| 9 |
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|
| 10 |
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|
| 11 |
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|
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|
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|
| 14 |
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|
| 15 |
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|
| 18 |
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|
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|
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| 21 |
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|
| 22 |
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|
| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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|
| 27 |
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|
| 28 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
| 33 |
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|
| 34 |
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|
| 35 |
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{
|
| 36 |
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|
| 37 |
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|
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|
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|
data/vals_ai/google/gemini-1.5-pro-002/4f2e817f-6b6d-48b2-8ce5-4be91e29d426.json
ADDED
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@@ -0,0 +1,792 @@
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|
| 1 |
+
{
|
| 2 |
+
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|
| 3 |
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|
| 4 |
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|
| 5 |
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"source_metadata": {
|
| 6 |
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"source_name": "Vals.ai Leaderboard - MGSM",
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| 7 |
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| 8 |
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|
| 9 |
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|
| 10 |
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"evaluator_relationship": "third_party",
|
| 11 |
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|
| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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|
| 16 |
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|
| 17 |
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|
| 18 |
+
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|
| 19 |
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}
|
| 20 |
+
},
|
| 21 |
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|
| 22 |
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"name": "Vals.ai",
|
| 23 |
+
"version": "unknown"
|
| 24 |
+
},
|
| 25 |
+
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|
| 26 |
+
"name": "gemini-1.5-pro-002",
|
| 27 |
+
"id": "google/gemini-1.5-pro-002",
|
| 28 |
+
"developer": "google",
|
| 29 |
+
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|
| 30 |
+
"vals_model_id": "google/gemini-1.5-pro-002",
|
| 31 |
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"vals_provider": "Google"
|
| 32 |
+
}
|
| 33 |
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},
|
| 34 |
+
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|
| 35 |
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{
|
| 36 |
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"evaluation_result_id": "mgsm:mgsm_bn:google/gemini-1.5-pro-002:score",
|
| 37 |
+
"evaluation_name": "vals_ai.mgsm.mgsm_bn",
|
| 38 |
+
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|
| 39 |
+
"dataset_name": "MGSM - Bengali",
|
| 40 |
+
"source_type": "url",
|
| 41 |
+
"url": [
|
| 42 |
+
"https://www.vals.ai/benchmarks/mgsm"
|
| 43 |
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|
| 44 |
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|
| 45 |
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"benchmark_slug": "mgsm",
|
| 46 |
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"task_key": "mgsm_bn",
|
| 47 |
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"dataset_type": "public",
|
| 48 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/mgsm"
|
| 49 |
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}
|
| 50 |
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|
| 51 |
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|
| 52 |
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|
| 53 |
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|
| 54 |
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|
| 55 |
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|
| 56 |
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|
| 57 |
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|
| 58 |
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|
| 59 |
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|
| 60 |
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|
| 61 |
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|
| 62 |
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|
| 63 |
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|
| 64 |
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"leaderboard_page_url": "https://www.vals.ai/benchmarks/mgsm"
|
| 65 |
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|
| 66 |
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|
| 67 |
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|
| 68 |
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|
| 69 |
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"details": {
|
| 70 |
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"benchmark_slug": "mgsm",
|
| 71 |
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|
| 72 |
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|
| 73 |
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|
| 74 |
+
"task_name": "Bengali",
|
| 75 |
+
"dataset_type": "public",
|
| 76 |
+
"industry": "math",
|
| 77 |
+
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|
| 78 |
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|
| 79 |
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|
| 80 |
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|
| 81 |
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|
| 82 |
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|
| 83 |
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|
| 84 |
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|
| 85 |
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|
| 86 |
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|
| 87 |
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|
| 88 |
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|
| 89 |
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|
| 90 |
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|
| 91 |
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|
| 92 |
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|
| 93 |
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|
| 94 |
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| 95 |
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|
| 96 |
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|
| 97 |
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|
| 98 |
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|
| 99 |
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"evaluation_result_id": "mgsm:mgsm_de:google/gemini-1.5-pro-002:score",
|
| 100 |
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"evaluation_name": "vals_ai.mgsm.mgsm_de",
|
| 101 |
+
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|
| 102 |
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|
| 103 |
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|
| 104 |
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"url": [
|
| 105 |
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|
| 106 |
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| 107 |
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|
| 108 |
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|
| 109 |
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|
| 110 |
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|
| 111 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/mgsm"
|
| 112 |
+
}
|
| 113 |
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},
|
| 114 |
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|
| 115 |
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"evaluation_description": "Accuracy reported by Vals.ai for MGSM (German).",
|
| 116 |
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"metric_id": "vals_ai.mgsm.mgsm_de.accuracy",
|
| 117 |
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"metric_name": "Accuracy",
|
| 118 |
+
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|
| 119 |
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|
| 120 |
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|
| 121 |
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|
| 122 |
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|
| 123 |
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|
| 124 |
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|
| 125 |
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| 126 |
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|
| 127 |
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"leaderboard_page_url": "https://www.vals.ai/benchmarks/mgsm"
|
| 128 |
+
}
|
| 129 |
+
},
|
| 130 |
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|
| 131 |
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"score": 91.2,
|
| 132 |
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"details": {
|
| 133 |
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"benchmark_slug": "mgsm",
|
| 134 |
+
"benchmark_name": "MGSM",
|
| 135 |
+
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|
| 136 |
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"task_key": "mgsm_de",
|
| 137 |
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|
| 138 |
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|
| 139 |
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|
| 140 |
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|
| 141 |
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|
| 142 |
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|
| 143 |
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|
| 144 |
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|
| 145 |
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"provider": "Google"
|
| 146 |
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|
| 147 |
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|
| 148 |
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|
| 149 |
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|
| 150 |
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|
| 151 |
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|
| 152 |
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|
| 153 |
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|
| 154 |
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| 155 |
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| 156 |
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| 157 |
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| 158 |
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| 159 |
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|
| 160 |
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|
| 161 |
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|
| 162 |
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| 163 |
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|
| 164 |
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|
| 165 |
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|
| 166 |
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|
| 167 |
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|
| 168 |
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|
| 169 |
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|
| 170 |
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| 171 |
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|
| 172 |
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|
| 173 |
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| 174 |
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| 175 |
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| 176 |
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| 177 |
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| 178 |
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| 179 |
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| 180 |
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|
| 181 |
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| 182 |
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| 183 |
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| 184 |
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| 185 |
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| 186 |
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|
| 187 |
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|
| 188 |
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| 189 |
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| 190 |
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"leaderboard_page_url": "https://www.vals.ai/benchmarks/mgsm"
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| 191 |
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|
| 192 |
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|
| 193 |
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|
| 194 |
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|
| 195 |
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| 196 |
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| 197 |
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|
| 198 |
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|
| 199 |
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|
| 200 |
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|
| 201 |
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|
| 202 |
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|
| 203 |
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|
| 204 |
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|
| 205 |
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|
| 206 |
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| 207 |
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| 209 |
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|
| 210 |
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| 211 |
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| 214 |
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| 215 |
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|
| 216 |
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|
| 217 |
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| 218 |
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| 219 |
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| 221 |
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|
| 223 |
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|
| 224 |
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|
| 225 |
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| 226 |
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| 227 |
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| 228 |
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|
| 229 |
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|
| 230 |
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| 231 |
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| 232 |
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| 234 |
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| 235 |
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| 236 |
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|
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data/vals_ai/google/gemini-1.5-pro-002/7635f61f-03d8-4879-9f76-5c870a56b2b2.json
ADDED
|
@@ -0,0 +1,288 @@
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|
|
|
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|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
|
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|
| 1 |
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{
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|
| 3 |
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data/vals_ai/google/gemini-1.5-pro-002/7e5903c6-0243-4a70-9eee-75d4c2b19c9e.json
ADDED
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data/vals_ai/google/gemini-1.5-pro-002/82982b53-113b-44fd-847f-ddbb3bf8dd94.json
ADDED
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@@ -0,0 +1,204 @@
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
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|
| 3 |
+
"evaluation_id": "vals-ai/aime/google_gemini-1.5-pro-002/1782803555.768981",
|
| 4 |
+
"retrieved_timestamp": "1782803555.768981",
|
| 5 |
+
"source_metadata": {
|
| 6 |
+
"source_name": "Vals.ai Leaderboard - AIME",
|
| 7 |
+
"source_type": "documentation",
|
| 8 |
+
"source_organization_name": "Vals.ai",
|
| 9 |
+
"source_organization_url": "https://www.vals.ai",
|
| 10 |
+
"evaluator_relationship": "third_party",
|
| 11 |
+
"additional_details": {
|
| 12 |
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|
| 13 |
+
"benchmark_name": "AIME",
|
| 14 |
+
"benchmark_updated": "2026-04-16",
|
| 15 |
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|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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}
|
| 20 |
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},
|
| 21 |
+
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|
| 22 |
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"name": "Vals.ai",
|
| 23 |
+
"version": "unknown"
|
| 24 |
+
},
|
| 25 |
+
"model_info": {
|
| 26 |
+
"name": "gemini-1.5-pro-002",
|
| 27 |
+
"id": "google/gemini-1.5-pro-002",
|
| 28 |
+
"developer": "google",
|
| 29 |
+
"additional_details": {
|
| 30 |
+
"vals_model_id": "google/gemini-1.5-pro-002",
|
| 31 |
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"vals_provider": "Google"
|
| 32 |
+
}
|
| 33 |
+
},
|
| 34 |
+
"evaluation_results": [
|
| 35 |
+
{
|
| 36 |
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"evaluation_result_id": "aime:aime_2024:google/gemini-1.5-pro-002:score",
|
| 37 |
+
"evaluation_name": "vals_ai.aime.aime_2024",
|
| 38 |
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"source_data": {
|
| 39 |
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"dataset_name": "AIME - AIME 2024",
|
| 40 |
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"source_type": "url",
|
| 41 |
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"url": [
|
| 42 |
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"https://www.vals.ai/benchmarks/aime"
|
| 43 |
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],
|
| 44 |
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"additional_details": {
|
| 45 |
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"benchmark_slug": "aime",
|
| 46 |
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"task_key": "aime_2024",
|
| 47 |
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"dataset_type": "public",
|
| 48 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/aime"
|
| 49 |
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}
|
| 50 |
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},
|
| 51 |
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"metric_config": {
|
| 52 |
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"evaluation_description": "Accuracy reported by Vals.ai for AIME (AIME 2024).",
|
| 53 |
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|
| 54 |
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|
| 55 |
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|
| 56 |
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|
| 57 |
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"lower_is_better": false,
|
| 58 |
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|
| 59 |
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|
| 60 |
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|
| 61 |
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|
| 62 |
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|
| 63 |
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"max_score_source": "fixed_percentage_bound",
|
| 64 |
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"leaderboard_page_url": "https://www.vals.ai/benchmarks/aime"
|
| 65 |
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}
|
| 66 |
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|
| 67 |
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"score_details": {
|
| 68 |
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"score": 23.75,
|
| 69 |
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"details": {
|
| 70 |
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"benchmark_slug": "aime",
|
| 71 |
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"benchmark_name": "AIME",
|
| 72 |
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"benchmark_updated": "2026-04-16",
|
| 73 |
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"task_key": "aime_2024",
|
| 74 |
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"task_name": "AIME 2024",
|
| 75 |
+
"dataset_type": "public",
|
| 76 |
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"industry": "math",
|
| 77 |
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"raw_score": "23.75",
|
| 78 |
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"raw_stderr": "0.755",
|
| 79 |
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"latency": "10.658",
|
| 80 |
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"cost_per_test": "0.00421",
|
| 81 |
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"provider": "Google"
|
| 82 |
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},
|
| 83 |
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"uncertainty": {
|
| 84 |
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|
| 85 |
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"value": 0.755,
|
| 86 |
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|
| 87 |
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}
|
| 88 |
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}
|
| 89 |
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}
|
| 90 |
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|
| 91 |
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{
|
| 92 |
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"evaluation_result_id": "aime:aime_2025:google/gemini-1.5-pro-002:score",
|
| 93 |
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"evaluation_name": "vals_ai.aime.aime_2025",
|
| 94 |
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"source_data": {
|
| 95 |
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"dataset_name": "AIME - AIME 2025",
|
| 96 |
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"source_type": "url",
|
| 97 |
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"url": [
|
| 98 |
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"https://www.vals.ai/benchmarks/aime"
|
| 99 |
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|
| 100 |
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|
| 101 |
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|
| 102 |
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|
| 103 |
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|
| 104 |
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"leaderboard_page_url": "https://www.vals.ai/benchmarks/aime"
|
| 105 |
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|
| 106 |
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},
|
| 107 |
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"metric_config": {
|
| 108 |
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"evaluation_description": "Accuracy reported by Vals.ai for AIME (AIME 2025).",
|
| 109 |
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"metric_id": "vals_ai.aime.aime_2025.accuracy",
|
| 110 |
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"metric_name": "Accuracy",
|
| 111 |
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"metric_kind": "accuracy",
|
| 112 |
+
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|
| 113 |
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"lower_is_better": false,
|
| 114 |
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|
| 115 |
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|
| 116 |
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|
| 117 |
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"additional_details": {
|
| 118 |
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"score_scale": "percent_0_to_100",
|
| 119 |
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|
| 120 |
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"leaderboard_page_url": "https://www.vals.ai/benchmarks/aime"
|
| 121 |
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}
|
| 122 |
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|
| 123 |
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"score_details": {
|
| 124 |
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"score": 13.75,
|
| 125 |
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"details": {
|
| 126 |
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|
| 127 |
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"benchmark_name": "AIME",
|
| 128 |
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"benchmark_updated": "2026-04-16",
|
| 129 |
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"task_key": "aime_2025",
|
| 130 |
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"task_name": "AIME 2025",
|
| 131 |
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"dataset_type": "public",
|
| 132 |
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"industry": "math",
|
| 133 |
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|
| 134 |
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|
| 135 |
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|
| 136 |
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"cost_per_test": "0.004196",
|
| 137 |
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|
| 138 |
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|
| 139 |
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|
| 140 |
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|
| 141 |
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|
| 142 |
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|
| 143 |
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|
| 144 |
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|
| 145 |
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|
| 146 |
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},
|
| 147 |
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{
|
| 148 |
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"evaluation_result_id": "aime:overall:google/gemini-1.5-pro-002:score",
|
| 149 |
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"evaluation_name": "vals_ai.aime.overall",
|
| 150 |
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"source_data": {
|
| 151 |
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"dataset_name": "AIME - Overall",
|
| 152 |
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"source_type": "url",
|
| 153 |
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"url": [
|
| 154 |
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"https://www.vals.ai/benchmarks/aime"
|
| 155 |
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|
| 156 |
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|
| 157 |
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"benchmark_slug": "aime",
|
| 158 |
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"task_key": "overall",
|
| 159 |
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"dataset_type": "public",
|
| 160 |
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"leaderboard_page_url": "https://www.vals.ai/benchmarks/aime"
|
| 161 |
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}
|
| 162 |
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},
|
| 163 |
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"metric_config": {
|
| 164 |
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"evaluation_description": "Accuracy reported by Vals.ai for AIME (Overall).",
|
| 165 |
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"metric_id": "vals_ai.aime.overall.accuracy",
|
| 166 |
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"metric_name": "Accuracy",
|
| 167 |
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"metric_kind": "accuracy",
|
| 168 |
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"metric_unit": "percent",
|
| 169 |
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|
| 170 |
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|
| 171 |
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|
| 172 |
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|
| 173 |
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|
| 174 |
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|
| 175 |
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|
| 176 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/aime"
|
| 177 |
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}
|
| 178 |
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},
|
| 179 |
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"score_details": {
|
| 180 |
+
"score": 18.75,
|
| 181 |
+
"details": {
|
| 182 |
+
"benchmark_slug": "aime",
|
| 183 |
+
"benchmark_name": "AIME",
|
| 184 |
+
"benchmark_updated": "2026-04-16",
|
| 185 |
+
"task_key": "overall",
|
| 186 |
+
"task_name": "Overall",
|
| 187 |
+
"dataset_type": "public",
|
| 188 |
+
"industry": "math",
|
| 189 |
+
"raw_score": "18.75",
|
| 190 |
+
"raw_stderr": "0.534",
|
| 191 |
+
"latency": "10.642",
|
| 192 |
+
"cost_per_test": "0.004203",
|
| 193 |
+
"provider": "Google"
|
| 194 |
+
},
|
| 195 |
+
"uncertainty": {
|
| 196 |
+
"standard_error": {
|
| 197 |
+
"value": 0.534,
|
| 198 |
+
"method": "vals_reported"
|
| 199 |
+
}
|
| 200 |
+
}
|
| 201 |
+
}
|
| 202 |
+
}
|
| 203 |
+
]
|
| 204 |
+
}
|
data/vals_ai/google/gemini-1.5-pro-002/8a615867-e648-4856-a8e0-33c86823304f.json
ADDED
|
@@ -0,0 +1,276 @@
|
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|
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|
|
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|
|
|
|
|
|
|
|
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|
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|
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|
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|
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|
|
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|
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|
|
|
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|
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|
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|
|
|
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|
|
|
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|
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|
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|
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|
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|
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|
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|
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|
|
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|
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|
|
|
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|
|
|
|
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|
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|
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|
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|
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|
|
|
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|
|
|
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|
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|
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|
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|
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|
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|
| 1 |
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|
| 2 |
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| 3 |
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| 5 |
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|
| 6 |
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| 7 |
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| 9 |
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| 10 |
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| 11 |
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| 35 |
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| 36 |
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| 156 |
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| 268 |
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| 272 |
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| 275 |
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|
| 276 |
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|
data/vals_ai/google/gemini-1.5-pro-002/8d504161-486f-4732-93cf-389cebc550d8.json
ADDED
|
@@ -0,0 +1,981 @@
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|
| 1 |
+
{
|
| 2 |
+
"schema_version": "0.2.2",
|
| 3 |
+
"evaluation_id": "vals-ai/mmlu_pro/google_gemini-1.5-pro-002/1782803555.768981",
|
| 4 |
+
"retrieved_timestamp": "1782803555.768981",
|
| 5 |
+
"source_metadata": {
|
| 6 |
+
"source_name": "Vals.ai Leaderboard - MMLU Pro",
|
| 7 |
+
"source_type": "documentation",
|
| 8 |
+
"source_organization_name": "Vals.ai",
|
| 9 |
+
"source_organization_url": "https://www.vals.ai",
|
| 10 |
+
"evaluator_relationship": "third_party",
|
| 11 |
+
"additional_details": {
|
| 12 |
+
"benchmark_slug": "mmlu_pro",
|
| 13 |
+
"benchmark_name": "MMLU Pro",
|
| 14 |
+
"benchmark_updated": "2026-06-17",
|
| 15 |
+
"dataset_type": "public",
|
| 16 |
+
"industry": "academic",
|
| 17 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/mmlu_pro",
|
| 18 |
+
"extraction_method": "static_astro_benchmark_view_props"
|
| 19 |
+
}
|
| 20 |
+
},
|
| 21 |
+
"eval_library": {
|
| 22 |
+
"name": "Vals.ai",
|
| 23 |
+
"version": "unknown"
|
| 24 |
+
},
|
| 25 |
+
"model_info": {
|
| 26 |
+
"name": "gemini-1.5-pro-002",
|
| 27 |
+
"id": "google/gemini-1.5-pro-002",
|
| 28 |
+
"developer": "google",
|
| 29 |
+
"additional_details": {
|
| 30 |
+
"vals_model_id": "google/gemini-1.5-pro-002",
|
| 31 |
+
"vals_provider": "Google"
|
| 32 |
+
}
|
| 33 |
+
},
|
| 34 |
+
"evaluation_results": [
|
| 35 |
+
{
|
| 36 |
+
"evaluation_result_id": "mmlu_pro:biology:google/gemini-1.5-pro-002:score",
|
| 37 |
+
"evaluation_name": "vals_ai.mmlu_pro.biology",
|
| 38 |
+
"source_data": {
|
| 39 |
+
"dataset_name": "MMLU Pro - Biology",
|
| 40 |
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data/vals_ai/google/gemini-1.5-pro-002/aa3c796d-e4ab-4c30-ba04-797de0a30464.json
ADDED
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data/vals_ai/google/gemini-1.5-pro-002/abab70b0-c577-4964-93e3-7795f9c3928a.json
ADDED
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|
| 1 |
+
{
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| 2 |
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| 9 |
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| 10 |
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|
| 11 |
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| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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| 16 |
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| 17 |
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|
| 18 |
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|
| 19 |
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|
| 20 |
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| 21 |
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| 22 |
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| 23 |
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"version": "unknown"
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| 24 |
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|
| 25 |
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|
| 26 |
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"name": "gemini-1.5-pro-002",
|
| 27 |
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"id": "google/gemini-1.5-pro-002",
|
| 28 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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| 33 |
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| 34 |
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|
| 35 |
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{
|
| 36 |
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|
| 37 |
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|
| 38 |
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|
| 39 |
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|
| 40 |
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|
| 41 |
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"url": [
|
| 42 |
+
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|
| 43 |
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| 44 |
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|
| 45 |
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| 46 |
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| 47 |
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| 48 |
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| 49 |
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| 50 |
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| 51 |
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| 52 |
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| 53 |
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| 54 |
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| 55 |
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| 56 |
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| 57 |
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| 58 |
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| 59 |
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| 60 |
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| 61 |
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| 62 |
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| 64 |
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| 65 |
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|
| 69 |
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|
| 70 |
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| 71 |
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|
| 72 |
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|
| 73 |
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|
| 74 |
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|
| 75 |
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|
| 76 |
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|
| 77 |
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| 78 |
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| 80 |
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| 81 |
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|
| 82 |
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| 83 |
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| 87 |
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| 88 |
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| 89 |
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| 94 |
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| 99 |
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| 100 |
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| 101 |
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| 102 |
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| 103 |
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| 104 |
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|
| 105 |
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| 109 |
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| 110 |
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|
| 111 |
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| 112 |
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| 113 |
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| 114 |
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|
| 115 |
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| 116 |
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| 117 |
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|
| 118 |
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| 119 |
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| 120 |
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|
| 121 |
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| 122 |
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| 123 |
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| 124 |
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| 125 |
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| 126 |
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| 127 |
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|
| 128 |
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|
| 129 |
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|
| 130 |
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|
| 131 |
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|
| 132 |
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|
| 133 |
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|
| 134 |
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| 135 |
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|
| 136 |
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| 137 |
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| 138 |
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| 139 |
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| 140 |
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| 142 |
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| 143 |
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| 144 |
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| 145 |
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| 146 |
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| 148 |
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| 149 |
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| 150 |
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| 151 |
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| 152 |
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| 153 |
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| 158 |
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| 159 |
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|
| 160 |
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| 161 |
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|
| 162 |
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|
| 163 |
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| 164 |
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| 165 |
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| 166 |
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| 167 |
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| 168 |
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| 169 |
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| 170 |
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| 171 |
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| 172 |
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| 173 |
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| 179 |
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| 180 |
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| 182 |
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| 183 |
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| 188 |
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| 190 |
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| 196 |
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| 197 |
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| 198 |
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| 200 |
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| 201 |
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| 202 |
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|
| 222 |
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| 225 |
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| 226 |
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| 228 |
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|
| 229 |
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|
| 230 |
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| 231 |
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| 232 |
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| 233 |
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|
| 234 |
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| 235 |
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| 240 |
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|
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| 257 |
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|
data/vals_ai/google/gemini-1.5-pro-002/ccc83c77-cdf6-4dff-a2af-8fdfd7994da0.json
ADDED
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@@ -0,0 +1,477 @@
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ADDED
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@@ -0,0 +1,216 @@
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|
| 179 |
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| 180 |
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| 181 |
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|
| 182 |
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|
| 183 |
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|
| 184 |
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|
| 185 |
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|
| 186 |
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|
| 187 |
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|
| 188 |
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|
| 189 |
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|
| 190 |
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|
| 191 |
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|
| 192 |
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|
| 193 |
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|
| 194 |
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|
| 195 |
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|
| 196 |
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|
| 197 |
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|
| 198 |
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|
| 199 |
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|
| 200 |
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|
| 201 |
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|
| 202 |
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|
| 203 |
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|
| 204 |
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|
| 205 |
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|
| 206 |
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|
| 207 |
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|
| 208 |
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|
| 209 |
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|
| 210 |
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|
| 211 |
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|
| 212 |
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|
| 213 |
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|
| 214 |
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|
| 215 |
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|
| 216 |
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|
data/vals_ai/google/gemini-1.5-pro-002/ff92616e-001f-403a-88d2-07ce2cf8cc95.json
ADDED
|
@@ -0,0 +1,216 @@
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|
|
| 1 |
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{
|
| 2 |
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|
| 3 |
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| 4 |
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| 5 |
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|
| 6 |
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| 7 |
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| 8 |
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| 9 |
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| 10 |
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|
| 11 |
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| 12 |
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| 13 |
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|
| 14 |
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|
| 15 |
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|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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|
| 20 |
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| 21 |
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|
| 22 |
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|
| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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|
| 27 |
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|
| 28 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
| 33 |
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|
| 34 |
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|
| 35 |
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|
| 36 |
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| 37 |
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|
| 71 |
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|
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|
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|
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|
| 156 |
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|
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|
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|
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|
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|
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|
| 190 |
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|
| 191 |
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|
| 192 |
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|
| 193 |
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|
| 194 |
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|
| 195 |
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|
| 196 |
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|
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|
| 198 |
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|
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|
| 200 |
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|
| 201 |
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|
| 202 |
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|
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|
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|
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|
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|
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|
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|
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|
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|
| 215 |
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|
| 216 |
+
}
|
data/vals_ai/google/gemini-2.0-flash-001/14c3feef-f7fc-49a4-b370-e10c78646af7.json
ADDED
|
@@ -0,0 +1,408 @@
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|
|
|
|
|
|
|
|
|
|
|
|
|
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|
| 1 |
+
{
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| 2 |
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|
| 9 |
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| 10 |
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|
| 11 |
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| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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| 16 |
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| 17 |
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|
| 18 |
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|
| 19 |
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|
| 20 |
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| 21 |
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| 22 |
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|
| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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"name": "gemini-2.0-flash-001",
|
| 27 |
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"id": "google/gemini-2.0-flash-001",
|
| 28 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
| 33 |
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|
| 34 |
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|
| 35 |
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{
|
| 36 |
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|
| 37 |
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|
| 38 |
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|
| 39 |
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|
| 40 |
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|
| 41 |
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"url": [
|
| 42 |
+
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|
| 43 |
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|
| 44 |
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|
| 45 |
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|
| 46 |
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| 47 |
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| 48 |
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| 49 |
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| 50 |
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| 51 |
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| 52 |
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| 53 |
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| 54 |
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| 55 |
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| 56 |
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| 57 |
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| 58 |
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| 59 |
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| 60 |
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| 61 |
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| 64 |
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| 65 |
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| 68 |
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|
| 69 |
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|
| 70 |
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|
| 71 |
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|
| 72 |
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|
| 73 |
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|
| 74 |
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|
| 75 |
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|
| 76 |
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|
| 77 |
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|
| 78 |
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|
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| 80 |
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| 81 |
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|
| 82 |
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|
| 83 |
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| 84 |
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| 85 |
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| 86 |
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|
| 87 |
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| 88 |
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| 89 |
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| 90 |
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| 91 |
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| 94 |
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| 95 |
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|
| 96 |
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| 97 |
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|
| 98 |
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| 99 |
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| 100 |
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| 101 |
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| 102 |
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| 103 |
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| 104 |
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|
| 105 |
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| 106 |
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| 107 |
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| 108 |
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| 109 |
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| 110 |
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|
| 111 |
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| 112 |
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|
| 113 |
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| 114 |
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|
| 115 |
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| 116 |
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|
| 117 |
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|
| 118 |
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| 119 |
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| 120 |
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|
| 121 |
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| 122 |
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| 123 |
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| 124 |
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| 125 |
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| 126 |
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|
| 127 |
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|
| 128 |
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|
| 129 |
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|
| 130 |
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|
| 131 |
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|
| 132 |
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|
| 133 |
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|
| 134 |
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|
| 135 |
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|
| 136 |
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|
| 137 |
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|
| 138 |
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| 139 |
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| 140 |
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| 141 |
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| 142 |
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| 143 |
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|
| 144 |
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| 145 |
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| 146 |
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| 147 |
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| 148 |
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| 149 |
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| 150 |
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|
| 151 |
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| 152 |
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| 153 |
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| 156 |
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| 157 |
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| 158 |
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|
| 159 |
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|
| 160 |
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| 161 |
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|
| 162 |
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|
| 163 |
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| 164 |
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| 165 |
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|
| 166 |
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| 167 |
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| 168 |
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| 169 |
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| 170 |
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| 171 |
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| 172 |
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| 173 |
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| 175 |
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| 176 |
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| 178 |
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| 179 |
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| 180 |
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| 181 |
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| 182 |
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| 183 |
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| 186 |
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| 188 |
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| 189 |
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| 190 |
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| 191 |
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| 192 |
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| 193 |
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|
| 196 |
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| 197 |
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| 198 |
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| 199 |
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| 200 |
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| 201 |
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| 202 |
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| 203 |
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| 204 |
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| 220 |
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|
| 221 |
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|
| 222 |
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| 223 |
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| 225 |
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| 226 |
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| 227 |
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|
| 228 |
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| 229 |
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data/vals_ai/google/gemini-2.0-flash-001/32c87288-dbd0-4b0c-b10f-615110169253.json
ADDED
|
@@ -0,0 +1,288 @@
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|
|
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|
| 1 |
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|
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data/vals_ai/google/gemini-2.0-flash-001/39454daa-ad55-452f-a9fd-30f95d80ddf8.json
ADDED
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@@ -0,0 +1,216 @@
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data/vals_ai/google/gemini-2.0-flash-001/3f54213b-2b24-4a9c-a3d6-1c2c16a52060.json
ADDED
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@@ -0,0 +1,225 @@
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| 128 |
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| 130 |
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| 131 |
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| 132 |
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| 133 |
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| 135 |
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| 155 |
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| 156 |
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| 158 |
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| 160 |
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|
| 161 |
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| 165 |
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| 167 |
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|
| 169 |
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| 172 |
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| 173 |
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| 174 |
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|
| 183 |
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|
| 184 |
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| 187 |
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| 188 |
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| 189 |
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| 190 |
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|
| 191 |
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| 192 |
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|
| 193 |
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|
| 194 |
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|
| 195 |
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|
| 196 |
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|
| 197 |
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|
| 198 |
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| 199 |
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| 200 |
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| 201 |
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|
| 202 |
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|
| 203 |
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|
| 204 |
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|
| 205 |
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|
| 206 |
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|
| 207 |
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| 208 |
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|
| 209 |
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|
| 210 |
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|
| 211 |
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|
| 212 |
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|
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| 214 |
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|
| 216 |
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|
| 217 |
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|
| 218 |
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|
| 219 |
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|
| 220 |
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|
| 221 |
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|
| 222 |
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|
| 223 |
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|
| 224 |
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|
| 225 |
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|
data/vals_ai/google/gemini-2.0-flash-001/6780858a-b0a5-4d52-b273-a01126dd746c.json
ADDED
|
@@ -0,0 +1,99 @@
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|
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|
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|
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|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
| 1 |
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| 2 |
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| 5 |
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| 9 |
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| 10 |
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|
| 11 |
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| 12 |
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| 13 |
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| 14 |
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| 15 |
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| 17 |
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| 18 |
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| 19 |
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| 20 |
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| 21 |
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| 22 |
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| 23 |
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| 27 |
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| 31 |
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| 32 |
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| 35 |
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| 36 |
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| 42 |
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| 73 |
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| 76 |
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| 99 |
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|
data/vals_ai/google/gemini-2.0-flash-001/6bd9c901-bd97-4f47-9dda-811857eb95ab.json
ADDED
|
@@ -0,0 +1,216 @@
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|
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|
| 1 |
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{
|
| 2 |
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|
| 3 |
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| 4 |
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| 5 |
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| 10 |
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|
| 11 |
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| 12 |
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| 13 |
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|
| 14 |
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| 15 |
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| 23 |
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|
| 26 |
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|
| 27 |
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|
| 28 |
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| 29 |
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|
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|
| 33 |
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|
| 35 |
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{
|
| 36 |
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data/vals_ai/google/gemini-2.0-flash-001/85735689-b835-41fe-ba96-c2987c64e3da.json
ADDED
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@@ -0,0 +1,276 @@
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|
| 1 |
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|
data/vals_ai/google/gemini-2.0-flash-001/9e750eb8-5989-42df-ab2e-89febc4e4e7c.json
ADDED
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@@ -0,0 +1,792 @@
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|
| 1 |
+
{
|
| 2 |
+
"schema_version": "0.2.2",
|
| 3 |
+
"evaluation_id": "vals-ai/mgsm/google_gemini-2.0-flash-001/1782803555.768981",
|
| 4 |
+
"retrieved_timestamp": "1782803555.768981",
|
| 5 |
+
"source_metadata": {
|
| 6 |
+
"source_name": "Vals.ai Leaderboard - MGSM",
|
| 7 |
+
"source_type": "documentation",
|
| 8 |
+
"source_organization_name": "Vals.ai",
|
| 9 |
+
"source_organization_url": "https://www.vals.ai",
|
| 10 |
+
"evaluator_relationship": "third_party",
|
| 11 |
+
"additional_details": {
|
| 12 |
+
"benchmark_slug": "mgsm",
|
| 13 |
+
"benchmark_name": "MGSM",
|
| 14 |
+
"benchmark_updated": "2026-01-09",
|
| 15 |
+
"dataset_type": "public",
|
| 16 |
+
"industry": "math",
|
| 17 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/mgsm",
|
| 18 |
+
"extraction_method": "static_astro_benchmark_view_props"
|
| 19 |
+
}
|
| 20 |
+
},
|
| 21 |
+
"eval_library": {
|
| 22 |
+
"name": "Vals.ai",
|
| 23 |
+
"version": "unknown"
|
| 24 |
+
},
|
| 25 |
+
"model_info": {
|
| 26 |
+
"name": "gemini-2.0-flash-001",
|
| 27 |
+
"id": "google/gemini-2.0-flash-001",
|
| 28 |
+
"developer": "google",
|
| 29 |
+
"additional_details": {
|
| 30 |
+
"vals_model_id": "google/gemini-2.0-flash-001",
|
| 31 |
+
"vals_provider": "Google"
|
| 32 |
+
}
|
| 33 |
+
},
|
| 34 |
+
"evaluation_results": [
|
| 35 |
+
{
|
| 36 |
+
"evaluation_result_id": "mgsm:mgsm_bn:google/gemini-2.0-flash-001:score",
|
| 37 |
+
"evaluation_name": "vals_ai.mgsm.mgsm_bn",
|
| 38 |
+
"source_data": {
|
| 39 |
+
"dataset_name": "MGSM - Bengali",
|
| 40 |
+
"source_type": "url",
|
| 41 |
+
"url": [
|
| 42 |
+
"https://www.vals.ai/benchmarks/mgsm"
|
| 43 |
+
],
|
| 44 |
+
"additional_details": {
|
| 45 |
+
"benchmark_slug": "mgsm",
|
| 46 |
+
"task_key": "mgsm_bn",
|
| 47 |
+
"dataset_type": "public",
|
| 48 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/mgsm"
|
| 49 |
+
}
|
| 50 |
+
},
|
| 51 |
+
"metric_config": {
|
| 52 |
+
"evaluation_description": "Accuracy reported by Vals.ai for MGSM (Bengali).",
|
| 53 |
+
"metric_id": "vals_ai.mgsm.mgsm_bn.accuracy",
|
| 54 |
+
"metric_name": "Accuracy",
|
| 55 |
+
"metric_kind": "accuracy",
|
| 56 |
+
"metric_unit": "percent",
|
| 57 |
+
"lower_is_better": false,
|
| 58 |
+
"score_type": "continuous",
|
| 59 |
+
"min_score": 0.0,
|
| 60 |
+
"max_score": 100.0,
|
| 61 |
+
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|
| 62 |
+
"score_scale": "percent_0_to_100",
|
| 63 |
+
"max_score_source": "fixed_percentage_bound",
|
| 64 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/mgsm"
|
| 65 |
+
}
|
| 66 |
+
},
|
| 67 |
+
"score_details": {
|
| 68 |
+
"score": 70.8,
|
| 69 |
+
"details": {
|
| 70 |
+
"benchmark_slug": "mgsm",
|
| 71 |
+
"benchmark_name": "MGSM",
|
| 72 |
+
"benchmark_updated": "2026-01-09",
|
| 73 |
+
"task_key": "mgsm_bn",
|
| 74 |
+
"task_name": "Bengali",
|
| 75 |
+
"dataset_type": "public",
|
| 76 |
+
"industry": "math",
|
| 77 |
+
"raw_score": "70.8",
|
| 78 |
+
"raw_stderr": "2.876",
|
| 79 |
+
"latency": "1.512",
|
| 80 |
+
"cost_per_test": "0.000133",
|
| 81 |
+
"max_output_tokens": "8192",
|
| 82 |
+
"provider": "Google"
|
| 83 |
+
},
|
| 84 |
+
"uncertainty": {
|
| 85 |
+
"standard_error": {
|
| 86 |
+
"value": 2.876,
|
| 87 |
+
"method": "vals_reported"
|
| 88 |
+
}
|
| 89 |
+
}
|
| 90 |
+
},
|
| 91 |
+
"generation_config": {
|
| 92 |
+
"generation_args": {
|
| 93 |
+
"max_tokens": 8192,
|
| 94 |
+
"max_attempts": 1
|
| 95 |
+
}
|
| 96 |
+
}
|
| 97 |
+
},
|
| 98 |
+
{
|
| 99 |
+
"evaluation_result_id": "mgsm:mgsm_de:google/gemini-2.0-flash-001:score",
|
| 100 |
+
"evaluation_name": "vals_ai.mgsm.mgsm_de",
|
| 101 |
+
"source_data": {
|
| 102 |
+
"dataset_name": "MGSM - German",
|
| 103 |
+
"source_type": "url",
|
| 104 |
+
"url": [
|
| 105 |
+
"https://www.vals.ai/benchmarks/mgsm"
|
| 106 |
+
],
|
| 107 |
+
"additional_details": {
|
| 108 |
+
"benchmark_slug": "mgsm",
|
| 109 |
+
"task_key": "mgsm_de",
|
| 110 |
+
"dataset_type": "public",
|
| 111 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/mgsm"
|
| 112 |
+
}
|
| 113 |
+
},
|
| 114 |
+
"metric_config": {
|
| 115 |
+
"evaluation_description": "Accuracy reported by Vals.ai for MGSM (German).",
|
| 116 |
+
"metric_id": "vals_ai.mgsm.mgsm_de.accuracy",
|
| 117 |
+
"metric_name": "Accuracy",
|
| 118 |
+
"metric_kind": "accuracy",
|
| 119 |
+
"metric_unit": "percent",
|
| 120 |
+
"lower_is_better": false,
|
| 121 |
+
"score_type": "continuous",
|
| 122 |
+
"min_score": 0.0,
|
| 123 |
+
"max_score": 100.0,
|
| 124 |
+
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|
| 125 |
+
"score_scale": "percent_0_to_100",
|
| 126 |
+
"max_score_source": "fixed_percentage_bound",
|
| 127 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/mgsm"
|
| 128 |
+
}
|
| 129 |
+
},
|
| 130 |
+
"score_details": {
|
| 131 |
+
"score": 91.6,
|
| 132 |
+
"details": {
|
| 133 |
+
"benchmark_slug": "mgsm",
|
| 134 |
+
"benchmark_name": "MGSM",
|
| 135 |
+
"benchmark_updated": "2026-01-09",
|
| 136 |
+
"task_key": "mgsm_de",
|
| 137 |
+
"task_name": "German",
|
| 138 |
+
"dataset_type": "public",
|
| 139 |
+
"industry": "math",
|
| 140 |
+
"raw_score": "91.6",
|
| 141 |
+
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|
| 142 |
+
"latency": "1.497",
|
| 143 |
+
"cost_per_test": "8.8e-05",
|
| 144 |
+
"max_output_tokens": "8192",
|
| 145 |
+
"provider": "Google"
|
| 146 |
+
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|
| 147 |
+
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|
| 148 |
+
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|
| 149 |
+
"value": 1.754,
|
| 150 |
+
"method": "vals_reported"
|
| 151 |
+
}
|
| 152 |
+
}
|
| 153 |
+
},
|
| 154 |
+
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|
| 155 |
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|
| 156 |
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"max_tokens": 8192,
|
| 157 |
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|
| 158 |
+
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|
| 159 |
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|
| 160 |
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|
| 161 |
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{
|
| 162 |
+
"evaluation_result_id": "mgsm:mgsm_en:google/gemini-2.0-flash-001:score",
|
| 163 |
+
"evaluation_name": "vals_ai.mgsm.mgsm_en",
|
| 164 |
+
"source_data": {
|
| 165 |
+
"dataset_name": "MGSM - English",
|
| 166 |
+
"source_type": "url",
|
| 167 |
+
"url": [
|
| 168 |
+
"https://www.vals.ai/benchmarks/mgsm"
|
| 169 |
+
],
|
| 170 |
+
"additional_details": {
|
| 171 |
+
"benchmark_slug": "mgsm",
|
| 172 |
+
"task_key": "mgsm_en",
|
| 173 |
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"dataset_type": "public",
|
| 174 |
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"leaderboard_page_url": "https://www.vals.ai/benchmarks/mgsm"
|
| 175 |
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}
|
| 176 |
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},
|
| 177 |
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|
| 178 |
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"evaluation_description": "Accuracy reported by Vals.ai for MGSM (English).",
|
| 179 |
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"metric_id": "vals_ai.mgsm.mgsm_en.accuracy",
|
| 180 |
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"metric_name": "Accuracy",
|
| 181 |
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|
| 182 |
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"metric_unit": "percent",
|
| 183 |
+
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|
| 184 |
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|
| 185 |
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|
| 186 |
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|
| 187 |
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|
| 188 |
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|
| 189 |
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"max_score_source": "fixed_percentage_bound",
|
| 190 |
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"leaderboard_page_url": "https://www.vals.ai/benchmarks/mgsm"
|
| 191 |
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}
|
| 192 |
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},
|
| 193 |
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"score_details": {
|
| 194 |
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"score": 95.6,
|
| 195 |
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"details": {
|
| 196 |
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"benchmark_slug": "mgsm",
|
| 197 |
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"benchmark_name": "MGSM",
|
| 198 |
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"benchmark_updated": "2026-01-09",
|
| 199 |
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"task_key": "mgsm_en",
|
| 200 |
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"task_name": "English",
|
| 201 |
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"dataset_type": "public",
|
| 202 |
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"industry": "math",
|
| 203 |
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"raw_score": "95.6",
|
| 204 |
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"raw_stderr": "1.297",
|
| 205 |
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"latency": "1.38",
|
| 206 |
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"cost_per_test": "8.9e-05",
|
| 207 |
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"max_output_tokens": "8192",
|
| 208 |
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"provider": "Google"
|
| 209 |
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|
| 210 |
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|
| 211 |
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|
| 212 |
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"value": 1.297,
|
| 213 |
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|
| 214 |
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|
| 215 |
+
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|
data/vals_ai/google/gemini-2.0-flash-001/a98d1b8f-32ce-4bb4-a010-55f3e1af3612.json
ADDED
|
@@ -0,0 +1,981 @@
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|
| 1 |
+
{
|
| 2 |
+
"schema_version": "0.2.2",
|
| 3 |
+
"evaluation_id": "vals-ai/mmlu_pro/google_gemini-2.0-flash-001/1782803555.768981",
|
| 4 |
+
"retrieved_timestamp": "1782803555.768981",
|
| 5 |
+
"source_metadata": {
|
| 6 |
+
"source_name": "Vals.ai Leaderboard - MMLU Pro",
|
| 7 |
+
"source_type": "documentation",
|
| 8 |
+
"source_organization_name": "Vals.ai",
|
| 9 |
+
"source_organization_url": "https://www.vals.ai",
|
| 10 |
+
"evaluator_relationship": "third_party",
|
| 11 |
+
"additional_details": {
|
| 12 |
+
"benchmark_slug": "mmlu_pro",
|
| 13 |
+
"benchmark_name": "MMLU Pro",
|
| 14 |
+
"benchmark_updated": "2026-06-17",
|
| 15 |
+
"dataset_type": "public",
|
| 16 |
+
"industry": "academic",
|
| 17 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/mmlu_pro",
|
| 18 |
+
"extraction_method": "static_astro_benchmark_view_props"
|
| 19 |
+
}
|
| 20 |
+
},
|
| 21 |
+
"eval_library": {
|
| 22 |
+
"name": "Vals.ai",
|
| 23 |
+
"version": "unknown"
|
| 24 |
+
},
|
| 25 |
+
"model_info": {
|
| 26 |
+
"name": "gemini-2.0-flash-001",
|
| 27 |
+
"id": "google/gemini-2.0-flash-001",
|
| 28 |
+
"developer": "google",
|
| 29 |
+
"additional_details": {
|
| 30 |
+
"vals_model_id": "google/gemini-2.0-flash-001",
|
| 31 |
+
"vals_provider": "Google"
|
| 32 |
+
}
|
| 33 |
+
},
|
| 34 |
+
"evaluation_results": [
|
| 35 |
+
{
|
| 36 |
+
"evaluation_result_id": "mmlu_pro:biology:google/gemini-2.0-flash-001:score",
|
| 37 |
+
"evaluation_name": "vals_ai.mmlu_pro.biology",
|
| 38 |
+
"source_data": {
|
| 39 |
+
"dataset_name": "MMLU Pro - Biology",
|
| 40 |
+
"source_type": "url",
|
| 41 |
+
"url": [
|
| 42 |
+
"https://www.vals.ai/benchmarks/mmlu_pro"
|
| 43 |
+
],
|
| 44 |
+
"additional_details": {
|
| 45 |
+
"benchmark_slug": "mmlu_pro",
|
| 46 |
+
"task_key": "biology",
|
| 47 |
+
"dataset_type": "public",
|
| 48 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/mmlu_pro"
|
| 49 |
+
}
|
| 50 |
+
},
|
| 51 |
+
"metric_config": {
|
| 52 |
+
"evaluation_description": "Accuracy reported by Vals.ai for MMLU Pro (Biology).",
|
| 53 |
+
"metric_id": "vals_ai.mmlu_pro.biology.accuracy",
|
| 54 |
+
"metric_name": "Accuracy",
|
| 55 |
+
"metric_kind": "accuracy",
|
| 56 |
+
"metric_unit": "percent",
|
| 57 |
+
"lower_is_better": false,
|
| 58 |
+
"score_type": "continuous",
|
| 59 |
+
"min_score": 0.0,
|
| 60 |
+
"max_score": 100.0,
|
| 61 |
+
"additional_details": {
|
| 62 |
+
"score_scale": "percent_0_to_100",
|
| 63 |
+
"max_score_source": "fixed_percentage_bound",
|
| 64 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/mmlu_pro"
|
| 65 |
+
}
|
| 66 |
+
},
|
| 67 |
+
"score_details": {
|
| 68 |
+
"score": 88.703,
|
| 69 |
+
"details": {
|
| 70 |
+
"benchmark_slug": "mmlu_pro",
|
| 71 |
+
"benchmark_name": "MMLU Pro",
|
| 72 |
+
"benchmark_updated": "2026-06-17",
|
| 73 |
+
"task_key": "biology",
|
| 74 |
+
"task_name": "Biology",
|
| 75 |
+
"dataset_type": "public",
|
| 76 |
+
"industry": "academic",
|
| 77 |
+
"raw_score": "88.703",
|
| 78 |
+
"raw_stderr": "1.182",
|
| 79 |
+
"latency": "2.946",
|
| 80 |
+
"cost_per_test": "0.000309",
|
| 81 |
+
"max_output_tokens": "8192",
|
| 82 |
+
"provider": "Google"
|
| 83 |
+
},
|
| 84 |
+
"uncertainty": {
|
| 85 |
+
"standard_error": {
|
| 86 |
+
"value": 1.182,
|
| 87 |
+
"method": "vals_reported"
|
| 88 |
+
}
|
| 89 |
+
}
|
| 90 |
+
},
|
| 91 |
+
"generation_config": {
|
| 92 |
+
"generation_args": {
|
| 93 |
+
"max_tokens": 8192,
|
| 94 |
+
"max_attempts": 1
|
| 95 |
+
}
|
| 96 |
+
}
|
| 97 |
+
},
|
| 98 |
+
{
|
| 99 |
+
"evaluation_result_id": "mmlu_pro:business:google/gemini-2.0-flash-001:score",
|
| 100 |
+
"evaluation_name": "vals_ai.mmlu_pro.business",
|
| 101 |
+
"source_data": {
|
| 102 |
+
"dataset_name": "MMLU Pro - Business",
|
| 103 |
+
"source_type": "url",
|
| 104 |
+
"url": [
|
| 105 |
+
"https://www.vals.ai/benchmarks/mmlu_pro"
|
| 106 |
+
],
|
| 107 |
+
"additional_details": {
|
| 108 |
+
"benchmark_slug": "mmlu_pro",
|
| 109 |
+
"task_key": "business",
|
| 110 |
+
"dataset_type": "public",
|
| 111 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/mmlu_pro"
|
| 112 |
+
}
|
| 113 |
+
},
|
| 114 |
+
"metric_config": {
|
| 115 |
+
"evaluation_description": "Accuracy reported by Vals.ai for MMLU Pro (Business).",
|
| 116 |
+
"metric_id": "vals_ai.mmlu_pro.business.accuracy",
|
| 117 |
+
"metric_name": "Accuracy",
|
| 118 |
+
"metric_kind": "accuracy",
|
| 119 |
+
"metric_unit": "percent",
|
| 120 |
+
"lower_is_better": false,
|
| 121 |
+
"score_type": "continuous",
|
| 122 |
+
"min_score": 0.0,
|
| 123 |
+
"max_score": 100.0,
|
| 124 |
+
"additional_details": {
|
| 125 |
+
"score_scale": "percent_0_to_100",
|
| 126 |
+
"max_score_source": "fixed_percentage_bound",
|
| 127 |
+
"leaderboard_page_url": "https://www.vals.ai/benchmarks/mmlu_pro"
|
| 128 |
+
}
|
| 129 |
+
},
|
| 130 |
+
"score_details": {
|
| 131 |
+
"score": 81.876,
|
| 132 |
+
"details": {
|
| 133 |
+
"benchmark_slug": "mmlu_pro",
|
| 134 |
+
"benchmark_name": "MMLU Pro",
|
| 135 |
+
"benchmark_updated": "2026-06-17",
|
| 136 |
+
"task_key": "business",
|
| 137 |
+
"task_name": "Business",
|
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data/vals_ai/google/gemini-2.0-flash-001/c14ecf63-06fc-4adf-897d-48a25349238e.json
ADDED
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@@ -0,0 +1,477 @@
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| 1 |
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{
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| 3 |
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| 477 |
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data/vals_ai/google/gemini-2.0-flash-001/c87b3ec1-7a1d-4560-8645-85a49f688348.json
ADDED
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@@ -0,0 +1,204 @@
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| 203 |
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| 204 |
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data/vals_ai/google/gemini-2.0-flash-001/fbc69c3d-519b-4f50-b641-b85d8c250f5a.json
ADDED
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@@ -0,0 +1,99 @@
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| 1 |
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|
| 10 |
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|
| 11 |
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| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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| 20 |
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|
| 21 |
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|
| 22 |
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|
| 23 |
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| 24 |
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| 25 |
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|
| 26 |
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|
| 27 |
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|
| 28 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
| 33 |
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|
| 34 |
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|
| 35 |
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|
| 36 |
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|
| 37 |
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|
| 38 |
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|
| 39 |
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|
| 40 |
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|
| 41 |
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|
| 42 |
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|
| 43 |
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|
| 44 |
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|
| 45 |
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|
| 46 |
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|
| 47 |
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|
| 48 |
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| 49 |
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| 51 |
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| 52 |
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| 53 |
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| 54 |
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| 55 |
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| 56 |
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|
| 57 |
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|
| 58 |
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|
| 59 |
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|
| 60 |
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|
| 61 |
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|
| 62 |
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|
| 63 |
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|
| 64 |
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|
| 65 |
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|
| 66 |
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|
| 67 |
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|
| 68 |
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|
| 69 |
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|
| 70 |
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|
| 71 |
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|
| 72 |
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|
| 73 |
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|
| 74 |
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|
| 75 |
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|
| 76 |
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|
| 77 |
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|
| 78 |
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|
| 79 |
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|
| 80 |
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|
| 81 |
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| 82 |
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|
| 83 |
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|
| 84 |
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|
| 85 |
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|
| 86 |
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|
| 87 |
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| 88 |
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| 89 |
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|
| 90 |
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|
| 91 |
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|
| 92 |
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|
| 93 |
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|
| 94 |
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|
| 95 |
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|
| 96 |
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|
| 97 |
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|
| 98 |
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|
| 99 |
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|
data/vals_ai/google/gemini-2.0-flash-exp/0edd0e94-356f-467a-8eb2-d1731327eb0d.json
ADDED
|
@@ -0,0 +1,99 @@
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|
|
|
|
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|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
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|
| 2 |
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|
| 3 |
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| 4 |
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| 5 |
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| 6 |
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| 7 |
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| 8 |
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|
| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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| 20 |
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| 21 |
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|
| 22 |
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|
| 23 |
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|
| 24 |
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| 25 |
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|
| 26 |
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|
| 27 |
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|
| 28 |
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| 29 |
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| 30 |
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|
| 31 |
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| 32 |
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| 33 |
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|
| 34 |
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|
| 35 |
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|
| 36 |
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|
| 37 |
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| 38 |
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|
| 39 |
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| 40 |
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| 41 |
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| 42 |
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|
| 43 |
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| 44 |
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| 45 |
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| 46 |
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|
| 47 |
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|
| 48 |
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| 49 |
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| 51 |
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| 52 |
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| 56 |
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| 57 |
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|
| 58 |
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|
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|
| 60 |
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|
| 61 |
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|
| 62 |
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| 64 |
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| 65 |
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| 67 |
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|
| 68 |
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|
| 69 |
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|
| 70 |
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|
| 71 |
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|
| 72 |
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|
| 73 |
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|
| 74 |
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|
| 75 |
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| 76 |
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|
| 77 |
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|
| 78 |
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|
| 79 |
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|
| 80 |
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| 81 |
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|
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| 84 |
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| 86 |
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| 88 |
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| 92 |
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| 93 |
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| 95 |
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|
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|
| 97 |
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|
| 98 |
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|
| 99 |
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|
data/vals_ai/google/gemini-2.0-flash-exp/3fd0a48d-98f8-4252-a624-a90d89e91c93.json
ADDED
|
@@ -0,0 +1,216 @@
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|
|
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|
|
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|
|
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|
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|
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|
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|
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|
|
|
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|
|
|
|
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|
|
|
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|
|
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|
|
|
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|
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|
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|
|
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|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
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{
|
| 2 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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| 8 |
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|
| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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|
| 16 |
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|
| 17 |
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| 18 |
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| 21 |
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| 22 |
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|
| 23 |
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|
| 24 |
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|
| 25 |
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|
| 26 |
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|
| 27 |
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|
| 28 |
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|
| 29 |
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|
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|
| 33 |
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|
| 34 |
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|
| 35 |
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{
|
| 36 |
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|
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|
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data/vals_ai/google/gemini-2.0-flash-exp/95074e1a-b052-4a19-b965-a760dd8e3934.json
ADDED
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@@ -0,0 +1,216 @@
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data/vals_ai/google/gemini-2.0-flash-thinking-exp-01-21/39409693-1438-4025-a6ff-41c8c695b98e.json
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| 165 |
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|
| 166 |
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| 167 |
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| 168 |
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| 169 |
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| 170 |
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| 171 |
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| 172 |
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| 173 |
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| 174 |
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|
| 175 |
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|
| 176 |
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| 177 |
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|
| 178 |
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|
| 179 |
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|
| 180 |
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|
| 181 |
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|
| 182 |
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|
| 183 |
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|
| 184 |
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|
| 185 |
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|
| 186 |
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|
| 187 |
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|
| 188 |
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|
| 189 |
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|
| 190 |
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|
| 191 |
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|
| 192 |
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|
| 193 |
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|
| 194 |
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|
| 195 |
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|
| 196 |
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|
| 197 |
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|
| 198 |
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| 199 |
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| 200 |
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|
| 201 |
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|
| 202 |
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|
| 203 |
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|
| 204 |
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| 205 |
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| 206 |
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| 207 |
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|
| 208 |
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|
| 209 |
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|
| 210 |
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| 211 |
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|
| 212 |
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|
| 213 |
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|
| 214 |
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|
| 215 |
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|
| 216 |
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|
data/vals_ai/google/gemini-2.0-flash-thinking-exp-01-21/5af204ba-31b0-4966-b1d0-b0e8bc39ee46.json
ADDED
|
@@ -0,0 +1,99 @@
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| 1 |
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| 9 |
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| 10 |
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| 11 |
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| 12 |
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| 13 |
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| 14 |
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| 15 |
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| 17 |
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| 18 |
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| 19 |
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| 20 |
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| 21 |
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| 22 |
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| 23 |
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| 26 |
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| 27 |
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| 28 |
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| 30 |
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| 31 |
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| 32 |
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| 33 |
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|
data/vals_ai/google/gemini-2.0-pro-exp-02-05/17466b64-ee76-4942-9926-aabdbfa839f0.json
ADDED
|
@@ -0,0 +1,216 @@
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|
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|
| 1 |
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{
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| 2 |
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| 5 |
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| 7 |
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| 9 |
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| 10 |
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|
| 11 |
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| 12 |
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|
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