CoolFace
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science-reasoning

reasoning-proj /judged_science_completionstabularn<1K2 likes1.4k downloads1y agoHugging Facereasoning-proj /severity_ablation_sciencetabular100K<n<1M0 likes1.4k downloads1y agoHugging Facedvilasuero /natural-science-reasoning Natural Sciences Reasoning: the "smolest" reasoning dataset A smol-scale open dataset for reasoning tasks using Hugging Face Inference Endpoints. While intentionally limited in scale, this resource prioritizes: Reproducible pipeline for reasoning tasks using a variety of models (Deepseek V3, Deepsek-R1, Llama70B-Instruct, etc.) Knowledge sharing for domains other than Math and Code reasoning In this repo, you can find: The prompts and the pipeline (see the config file). The… See the full description on the dataset page: https://huggingface.co/datasets/dvilasuero/natural-science-reasoning.texttext-generationn<1K40 likes697 downloads2y agoHugging Facereasoning-proj /science_traces_original_DeepSeek-R1-Distill-Qwen-32Btextn<1K0 likes426 downloads1y agoHugging Facelaion /llama-nemotron-science-reasoning-on-canonical-think-full Llama-Nemotron science reasoning — Delphi canonical-think (COMPLETE, no length filter) The complete reasoning:on science split of nvidia/Llama-Nemotron-Post-Training-Dataset, converted once into the canonical Delphi chat-template thinking format. 708,920 rows. Unlike the cold-start warmup slice open-athena/llama-nemotron-science-reasoning-on-le3000tok-100k (and its -canonical-think variant), this build applies no length cap and no subsample — every long-CoT science example is… See the full description on the dataset page: https://huggingface.co/datasets/laion/llama-nemotron-science-reasoning-on-canonical-think-full.texttext-generation100K<n<1M0 likes379 downloads18d agoHugging Faceseonjeongh /science_reasoning science_reasoning Mistral-7B의 과학 지식·추론 능력 향상을 위해 6개 공개 과학 객관식 QA 데이터셋을 통일 포맷으로 변환하고, ARC-Challenge test와의 오염을 제거한 데이터셋입니다. 원본 데이터셋 allenai/sciq allenai/openbookqa (main) allenai/qasc allenai/quartz allenai/ai2_arc (ARC-Easy / ARC-Challenge) nguyen-brat/worldtree 전처리 포맷 통일: 각 데이터셋의 서로 다른 스키마를 unique_id, orig_id, source, question, choices, answer, support 필드로 변환. support는 근거 문단/문장으로, 데이터셋별 원본 필드(support/fact/para/cot)에서 구성하거나 없으면 빈 문자열.… See the full description on the dataset page: https://huggingface.co/datasets/seonjeongh/science_reasoning.textmultiple-choice10K<n<100K0 likes333 downloads2mo agoHugging Face