datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
DeepSeek-v3.1-reasoner-Distilled-math-samples
DeepSeek-V3.1 Distillation with NVIDIA Nemotron-Post-Training-Dataset-v2 (Math Subset)
The release of DeepSeek-V3.1 has attracted wide attention in the AI community. Its significant improvements in reasoning ability provide a new opportunity to explore optimization of domain-specific models. To investigate the potential of this model in complex mathematical reasoning tasks, I selected the math subset from NVIDIA’s newly released Nemotron-Post-Training-Dataset-v2 as seed problems and… See the full description on the dataset page: https://huggingface.co/datasets/Jackrong/DeepSeek-v3.1-reasoner-Distilled-math-samples.popqa-olmo-3-7b-instruct-temp0.9-samples99-logprobs
OLMo-3-7B-Instruct self-consistency generations with logprobs on PopQA
This dataset contains 99 self-consistency generations per question for the
PopQA benchmark, produced with allenai/OLMo-3-7B-Instruct at temperature
0.9, together with token-level log probabilities for each completion.
The file is intended for post-hoc analysis, self-consistency curves, adaptive
stopping, and related aggregation methods.
Source
Base benchmark: PopQA
Model: allenai/OLMo-3-7B-Instruct… See the full description on the dataset page: https://huggingface.co/datasets/s-nlp/popqa-olmo-3-7b-instruct-temp0.9-samples99-logprobs.QA_hukum_samplesThis dataset sample was constructed by generating QA pairs from Law No. 17 of 2008 on Shipping (Undang-Undang No 17 Tahun 2008 Tentang Pelayaran). It is then manually verified by human validators and reviewers, resulting in QA pairs with fine-grained label categories.