datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Convergent-7B-data
Convergent-7B Training Data
Training data for the bigcompute.science research companion model.
Early Preview — This dataset is a work in progress. It is expressly designed to train a research assistant for the bigcompute.science MCP server as part of the Convergent conjecture-driven GPU research project. The dataset will be updated frequently as new experiments, findings, and tool definitions are added. Expect changes to schema, tool names, and content until we reach a GA… See the full description on the dataset page: https://huggingface.co/datasets/cahlen/Convergent-7B-data.math500-olmo-3-7b-instruct-temp0.9-samples99-logprobs
OLMo-3-7B-Instruct self-consistency generations with logprobs on MATH500
This dataset contains 99 self-consistency generations per question for the
MATH500 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: HuggingFaceH4/MATH-500
Model:… See the full description on the dataset page: https://huggingface.co/datasets/s-nlp/math500-olmo-3-7b-instruct-temp0.9-samples99-logprobs.Llama2-7B-data-course
Dataset Description
This dataset is designed to support a teaching assistance model for an introductory computer science course. It includes structured content such as course syllabi, lesson plans, lecture materials, and exercises related to topics such as computer fundamentals, algorithms, hardware, software, and IT technologies. The dataset integrates practical assignments, theoretical knowledge, and ethical education, aiming to enhance teaching efficiency and improve student… See the full description on the dataset page: https://huggingface.co/datasets/2imi9/Llama2-7B-data-course.Mistral-7b-0.3-Instruct-TriviaQA-HighlyKnownDataset for paper “How Much Knowledge Can You Pack into a LoRA Adapter without Harming LLM?”
Based on TriviaQA dataset
(https://huggingface.co/papers/2502.14502)
Mistral-7b-0.3-Instruct-DBpedia-HighlyKnownDataset for paper “How Much Knowledge Can You Pack into a LoRA Adapter without Harming LLM?”
Based on DBpedia dataset
Paper, Code
das-dpo-data-searchr1-7b
DAS dpo data-searchr1-7b
This dataset provides DPO preference data for post-training SearchR1 7B search agents with DAS.
The file is provided in LLaMA-Factory compatible DPO format with prompt, chosen, rejected, and optional system fields.
Medical-QA-Mistral7B-FinetuningLlama-2-7b-chat-finetune
plagas y enfermedades en el cultivo del tomate Dataset 1000
Dataset de 1000 instrucciones sobre la plagas y enfermedades en el cultivo del tomate.
Uso
from datasets import load_dataset
dataset = load_dataset("anyerg21/plagas-enfermedades-tomate-1000")
Estructura
instruction: Pregunta sobre el cultivo del tomate
input: Campo vacio
output: Respuesta
category: Categoria tematica
question_type: Tipo de pregunta
difficulty: Nivel de dificultad
Ejemplo… See the full description on the dataset page: https://huggingface.co/datasets/anyerg21/Llama-2-7b-chat-finetune.SampleLlama2_7b_data
Dataset Card for Dataset Name
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
Dataset Details
Dataset Description
Curated by: [More Information Needed]
Funded by [optional]: [More Information Needed]
Shared by [optional]: [More Information Needed]
Language(s) (NLP): [More Information Needed]
License: [More Information Needed]
Dataset Sources [optional]
Repository: [More… See the full description on the dataset page: https://huggingface.co/datasets/TaJ001/SampleLlama2_7b_data.chatbot-arena-ja-calm2-7b-chat-experimental_dedupedchatbot-arena-ja-calm2-7b-chatからpromptが一致するデータを削除したデータセットです。
DeepScale-qwen2.5_7b-multi使用Qwen2.5-7b-Instruct模型，从DeepScaler数据集中抽取20000条数据，使用多轮对话的方式获得数学答案。
prompt模板：
使用的system_prompt是LLAMA_MATH_SYSTEM_PROMPT
多轮对话的prompt是ITER_GEN_MULTI_TURN_STEP_PROMPTS
LLAMA_MATH_SYSTEM_PROMPT = """
Solve the following math problem efficiently and clearly:
- For simple problems (2 steps or fewer):
Provide a concise solution with minimal explanation.
- For complex problems (3 steps or more):
Use this step-by-step format:
## Step 1: [Concise description]
[Brief explanation and calculations]
##… See the full description on the dataset page: https://huggingface.co/datasets/tttonyyy/DeepScale-qwen2.5_7b-multi.modelbest-Qwen-2.5-Omni-7B-SFT-with-DPO-dataset_for_DPO
OminiGAIA-DPO-data
This dataset contains the final DPO training pairs used to train
ZhangYuchi/modelbest-Qwen-2.5-Omni-7B-SFT-with-DPO.
The pairs are derived from 7B-native rollouts on OmniGAIA train questions:
Roll out the SFT model on answer-hidden train inputs.
Audit each rollout with Gemini using the private reference answer and annotated solution.
Locate the first erroneous assistant sub-step.
Convert the corrected prefix (tau_win) and the original erroneous prefix… See the full description on the dataset page: https://huggingface.co/datasets/ZhangYuchi/modelbest-Qwen-2.5-Omni-7B-SFT-with-DPO-dataset_for_DPO.hotpotqa-dev-olmo-3-7b-instruct-temp0.9-samples99-logprobs
OLMo-3-7B-Instruct self-consistency generations with logprobs on HotpotQA
This dataset contains 99 self-consistency generations per question for the
HotpotQA validation split, 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: hotpotqa/hotpot_qa… See the full description on the dataset page: https://huggingface.co/datasets/s-nlp/hotpotqa-dev-olmo-3-7b-instruct-temp0.9-samples99-logprobs.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.qwen_7B_pairs.jsonAn example preference pairs dataset for DPO. This dataset is prompted on fine-tuned qwen_7B. Check https://github.com/CatIIIIIIII/VeriPrefer for usage.
ugphysics-synthetic-qwen7b
UGPhysics Synthetic Dataset (Qwen 7B)
Synthetic physics dataset with 4,703 examples generated using Qwen2.5-7B-Instruct.
Columns
question, ground_truth, solution, final, verdict, is_correct, critique
sft_prompt, sft_target, solver_model, critic_model
Usage
from datasets import load_dataset
ds = load_dataset("Rbaudeu/ugphysics-synthetic-qwen7b", split="train")
mmlu-pro-olmo-3-7b-instruct-temp0.9-samples99-logprobs
OLMo-3-7B-Instruct self-consistency generations with logprobs on MMLU-Pro
This dataset contains 99 self-consistency generations per question for the
MMLU-Pro test split, 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: TIGER-Lab/MMLU-Pro
Model:… See the full description on the dataset page: https://huggingface.co/datasets/s-nlp/mmlu-pro-olmo-3-7b-instruct-temp0.9-samples99-logprobs.