| operators: |
| - id: load_math |
| config: |
| type: hf_source |
| dataset: open-web-math/open-web-math |
| split: train |
| trust_remote_code: True |
| - id: sample_dataset |
| config: |
| type: function |
| function: data_strategies.commons.uniform_sample_fixed |
| function_config: |
| num_samples: 50_000 |
| input_ids: |
| - load_math |
| - id: generate_instructions |
| config: |
| type: completions |
| map: chat |
| 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 |
| require_all_responses: False |
| batch: True |
| input_ids: |
| - sample_dataset |
| - id: add_constant_column |
| config: |
| type: function |
| function: data_strategies.commons.add_constant_columns |
| function_config: |
| response_seed: "" |
| input_ids: |
| - generate_instructions |
| - id: drop_columns |
| config: |
| type: function |
| function: data_strategies.commons.keep_only_columns |
| function_config: |
| columns_to_keep: |
| - instruction_seed |
| - response_seed |
| input_ids: |
| - add_constant_column |
| - 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: 80.0 |
| ngram_size: 13 |
| input_ids: |
| - drop_columns |
| - id: sample_dataset_final |
| config: |
| type: function |
| function: data_strategies.commons.uniform_sample_fixed |
| function_config: |
| num_samples: 31_600 |
| input_ids: |
| - decontaminate |
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