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config/load_in_science_cqadupstack.yaml

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+operators:
+- id: load_hf
+  config:
+    type: hf_source
+    dataset: mteb/cqadupstack-physics
+    split: corpus
+    subset: corpus
+- id: over_sample_dataset
+  config:
+    type: function
+    function: data_strategies.commons.uniform_sample_fixed
+    function_config:
+      num_samples: 1_100_000
+  input_ids:
+  - load_hf
+- id: generate_instructions
+  config:
+    type: completions
+    map: chat
+    map_config:
+      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 Biology, Physics or Chemistry Olympiad. 
+
+        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
+    batch: true
+  input_ids:
+    - over_sample_dataset
+
+- id: add_source_name
+  config:
+    type: function
+    function: data_strategies.commons.add_constant_columns
+    function_config:
+      _source: "cqadupstack-physics"
+  input_ids:
+  - generate_instructions
+- id: upsample_dataset
+  config:
+    type: function
+    function: data_strategies.commons.upsample_dataset
+    function_config:
+      num_samples: 1_100_000
+  input_ids:
+  - add_source_name
+# - id: decontaminate
+#   config:
+#     type: cpu_function
+#     sharded: false
+#     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
+#   config:
+#     type: function
+#     function: data_strategies.commons.uniform_sample_limited
+#     function_config:
+#       num_samples: 1_000_000
+#   input_ids: ["decontaminate"]