datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.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.QWENMillenium-SF-Science-Analytics-Reasoning
QWENMillenium-SF
Dataset 1 of 5 in the Atem Training Pipeline
QWENMillenium-SF is a supervised fine-tuning (SFT) dataset of 5,000
analytical and scientific reasoning examples generated by
Qwen/Qwen2.5-14B-Instruct with structured chain-of-thought prompting.
It forms the first component of the distillation pipeline used to train
Atem, a Qwen2.5-1.5B-based model targeting analytical reasoning
performance beyond its parameter class.
The Atem Pipeline
Atem is a… See the full description on the dataset page: https://huggingface.co/datasets/EphAsad/QWENMillenium-SF-Science-Analytics-Reasoning.llama-nemotron-science-reasoning-on-le3000tok-100k
Llama-Nemotron science reasoning — Delphi cold-start CoT warmup (≤3000 tok, reasoning:on, 100k)
A filtered subsample of nvidia/Llama-Nemotron-Post-Training-Dataset built to
warm up the Delphi chat-template reasoning tokens (<|start_think|> / <|end_think|>) during
cold-start SFT (marin #6279). It is a template/CoT warmup slice, not a knowledge dataset.
Filtering applied (this is the whole point of the repo)
Starting from nvidia/Llama-Nemotron-Post-Training-Dataset:… See the full description on the dataset page: https://huggingface.co/datasets/open-athena/llama-nemotron-science-reasoning-on-le3000tok-100k.llama-nemotron-science-reasoning-on-le3000tok-100k-canonical-think
Llama-Nemotron science reasoning — Delphi cold-start CoT warmup (canonical think tokens)
Regenerated (Fix C) variant of
laion/llama-nemotron-science-reasoning-on-le3000tok-100k.
The original repo's assistant turns carry inline <think>...</think>. LLaMA-Factory's
ReasoningTemplate.encode_oneturn checks for the literal canonical string <|start_think|>
in the assistant content; inline <think> does NOT satisfy that check, so LF injects an EMPTY
canonical block… See the full description on the dataset page: https://huggingface.co/datasets/open-athena/llama-nemotron-science-reasoning-on-le3000tok-100k-canonical-think.