jamesdborin/Nemotron-Math-Science-and-Technical-Reasoning-prompt-only
Math, Science and Technical Reasoning Prompt-Only This dataset combines prompt-only datasets by capability theme for distillation experiments. It contains 2,872,847 unique prompts from 16,068,969 raw rows; 13,196,122 exact canonical duplicates were removed. Rows retain the canonical prompt-extraction columns and add source_repo_id for provenance. Deduplication uses normalized system_prompt, prompt, tools, and schema_str, with the first row in manifest order retained. Original… See the full description on the dataset page: https://huggingface.co/datasets/jamesdborin/Nemotron-Math-Science-and-Technical-Reasoning-prompt-only.
Math, Science and Technical Reasoning Prompt-Only
This dataset combines prompt-only datasets by capability theme for distillation experiments. It contains 2,872,847 unique prompts from 16,068,969 raw rows; 13,196,122 exact canonical duplicates were removed.
Rows retain the canonical prompt-extraction columns and add source_repo_id for provenance. Deduplication uses normalized system_prompt, prompt, tools, and schema_str, with the first row in manifest order retained. Original source licenses and usage conditions continue to apply.
Sources
- jamesdborin/Nemotron-Math-Proofs-v1-prompt-only: 1,376,663 raw prompts
- jamesdborin/Nemotron-Math-Proofs-v2-prompt-only: 82,737 raw prompts
- jamesdborin/Nemotron-Math-v2-prompt-only: 7,085,839 raw prompts
- jamesdborin/Nemotron-RL-Math-v2-prompt-only: 3,748 raw prompts
- jamesdborin/Nemotron-SFT-Math-v3-prompt-only: 3,638,783 raw prompts
- jamesdborin/Nemotron-SFT-Math-v4-prompt-only: 545,431 raw prompts
- jamesdborin/Nemotron-RL-Science-v1-prompt-only: 150,644 raw prompts
- jamesdborin/Nemotron-SFT-Science-v2-prompt-only: 2,837,712 raw prompts
- jamesdborin/Nemotron-RL-litmus-bench-v0.1-prompt-only: 5,714 raw prompts
- jamesdborin/Nemotron-RL-ReasoningGym-v1-prompt-only: 15,000 raw prompts
- jamesdborin/Nemotron-SpecializedDomains-Finance-v1-prompt-only: 326,698 raw prompts
See merge_report.json for per-source parsed, retained, duplicate, and output-size counts.
Doubleword batch splits
Model-agnostic JSONL requests use model: "[MODEL]" and are ready for dw files prepare.
small: 100,000 requestsmedium: 500,000 requestslarge: 1,000,000 requests
