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config/load_in_math_automathtext.yaml

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+operators: 
+- id: load_math
+  config:
+    type: hf_source
+    dataset: math-ai/AutoMathText
+    split: train
+    trust_remote_code: True
+- id: sample_dataset
+  config:
+    type: function
+    function: data_strategies.commons.uniform_sample_fixed
+    function_config:
+      num_samples: 1_100_000
+  input_ids:
+  - load_math
+- id: add_constant_column
+  config:
+    type: function
+    function: data_strategies.commons.add_constant_columns
+    function_config:
+      response_seed: ""
+  input_ids:
+  - sample_dataset
+- id: generate_instructions
+  config:
+    type: completions
+    map: chat
+    require_all_responses: false
+    map_config:
+      system_message: "You are a helpful assistant."
+      user_message: |
+        You are to reform the following math text snippet into a question with a quantitative or verifiable answer such as one that would be 
+        included in the USAMO or the Putnam Exam. 
+
+        Text: {{text}}
+        
+        Include only the new question or task. Do not include anything like "Here is the instruction". You can either extract a 
+        question from the text or form a new one based on the text. Make the question sound like what a human would ask a language model. 
+      output_column: instruction_seed
+    model: gpt-4o-mini
+    temperature: 1.0
+  input_ids:
+  - sample_dataset
+- id: add_source_name
+  config:
+    type: function
+    function: data_strategies.commons.add_constant_columns
+    function_config:
+      _source: "math-ai/AutoMathText"
+  input_ids:  
+  - generate_instructions
+# - id: decontaminate
+#   config:
+#     type: cpu_function
+#     sharded: true
+#     num_shards: 8
+#     num_cpus: 32
+#     function:  data_strategies._A1_Source.utils.decontaminate_fuzzy_w_ngram
+#     function_config:
+#       column: instruction_seed
+#       eval_datasets:
+#         - HuggingFaceH4/MATH-500
+#         - Maxwell-Jia/AIME_2024
+#         - AI-MO/aimo-validation-amc
+#         - livecodebench/code_generation_lite
+#         - mlfoundations-dev/AIME2025_combined
+#         - cais/hle
+#         - open-r1/codeforces
+#         - Idavidrein/gpqa
+#         - daman1209arora/jeebench
+#         - mlfoundations-dev/mmlu_pro_eval_full
+#         - Qwen/CodeElo
+#         - open-r1/ioi
+#       eval_columns:
+#         - problem
+#         - Problem
+#         - problem
+#         - question_content
+#         - question
+#         - question
+#         - description
+#         - Question
+#         - question
+#         - prompt
+#         - description
+#         - statement
+#       eval_splits:
+#         - test
+#         - train
+#         - train
+#         - test
+#         - train
+#         - test
+#         - test
+#         - train
+#         - test
+#         - test
+#         - test
+#         - test
+#       eval_subsets:
+#         Idavidrein/gpqa: gpqa_diamond
+#       similarity_threshold: 75.0
+#       ngram_size: 13
+#   input_ids:
+#   - add_source_name
+- id: sample_dataset_final
+  config:
+    type: function
+    function: data_strategies.commons.uniform_sample_limited
+    function_config:
+      num_samples: 1_000_000
+  input_ids: ["add_source_name"]
+