datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ReAPR-Automatic-Program-Repair-via-Retrieval-Augmented-Large-Language-ModelsThis is the Retrieval dataset used in the paper "ReAPR: Automatic Program Repair via Retrieval-Augmented Large Language Models"
Baize-TCM-Corpus-for-Large-Language-Models-V3
白泽中医药大模型语料库
版本：3.0语料数量：157,438 条语言：中文领域：中医药（Traditional Chinese Medicine, TCM）格式：问答对（QA Pair）用途：中医药大模型训练、知识问答系统、语义理解研究
📚 简介
“白泽中医药大模型语料库”是一个专注于中医药领域的高质量问答语料集合，旨在支持中医药知识的数字化、智能化应用。语料库共包含 157,438 条 经过整理与校对的问答对，涵盖中医基础理论、中药学、方剂学、诊断学、针灸推拿、经典医籍、临床实践等多个子领域。
本语料库可广泛应用于：
中医药大语言模型的预训练与微调
智能问答系统开发
医学自然语言处理任务（如实体识别、关系抽取）
中医药知识图谱构建
🧩 数据内容
每条语料为一个标准的问答对，格式如下：
{
"instruction": "广义转录组和狭义转录组在定义上的主要区别是什么？",
"input": "",
"output":… See the full description on the dataset page: https://huggingface.co/datasets/DigitalIntelligenceCenter-of-ICMM/Baize-TCM-Corpus-for-Large-Language-Models-V3.Instruction-Following-Evaluation-for-Large-Language-Models
Instruction-Following Evaluation Dataset
📜 Overview
This dataset, specifically designed for the evaluation of large language models in instruction-following tasks, is directly inspired by the methodologies and experiments described in the paper titled "Instruction-Following Evaluation for Large Language Models". The dataset's creation and availability on HuggingFace are aimed at enhancing research and application in the field of natural language understanding… See the full description on the dataset page: https://huggingface.co/datasets/harpreetsahota/Instruction-Following-Evaluation-for-Large-Language-Models.Towards-Joint-Modeling-of-Dialogue-Response-and-Speech-Synthesis-based-on-Large-Language-Modeldetails_mervinpraison__tamil-large-language-model-7b-v1.0
Dataset Card for Evaluation run of mervinpraison/tamil-large-language-model-7b-v1.0
Dataset automatically created during the evaluation run of model mervinpraison/tamil-large-language-model-7b-v1.0 on the Open LLM Leaderboard.
The dataset is composed of 63 configuration, each one coresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard-old/details_mervinpraison__tamil-large-language-model-7b-v1.0.Baize-TCM-Corpus-for-Large-Language-Models-V2
白泽中医药大模型语料库
版本：2.0语料数量：10.578 条语言：中文领域：中医药（Traditional Chinese Medicine, TCM）格式：问答对（QA Pair）用途：中医药大模型训练、知识问答系统、语义理解研究
📚 简介
“白泽中医药大模型语料库”是一个专注于中医药领域的高质量问答语料集合，旨在支持中医药知识的数字化、智能化应用。语料库共包含 10,578 条 经过整理与校对的问答对，涵盖中医基础理论、中药学、方剂学、诊断学、针灸推拿、经典医籍、临床实践等多个子领域。
本语料库可广泛应用于：
中医药大语言模型的预训练与微调
智能问答系统开发
医学自然语言处理任务（如实体识别、关系抽取）
中医药知识图谱构建
🧩 数据内容
每条语料为一个标准的问答对，格式如下：
{
"instruction": "广义转录组和狭义转录组在定义上的主要区别是什么？",
"input": "",
"output":… See the full description on the dataset page: https://huggingface.co/datasets/DigitalIntelligenceCenter-of-ICMM/Baize-TCM-Corpus-for-Large-Language-Models-V2.FeatureCoding-LargeLanguageModel
lm-evaluation-harness: https://github.com/EleutherAI/lm-evaluation-harness/tree/v0.4.10
Qwen3-8B: https://huggingface.co/Qwen/Qwen3-8B
FalconMamba-7B: https://huggingface.co/tiiuae/falcon-mamba-7b-instruct
@misc{pang2026largemodelfeaturecoding,
title={Towards Large Model Feature Coding},
author={Youwei Pang and Changsheng Gao and Dong Liu and Huchuan Lu and Weisi Lin},
year={2026},
eprint={2605.24025},
archivePrefix={arXiv},
primaryClass={cs.CV}… See the full description on the dataset page: https://huggingface.co/datasets/Yoweey/FeatureCoding-LargeLanguageModel.Baize-TCM-Corpus-for-Large-Language-Models-V1
白泽中医药大模型语料库
版本：1.0语料数量：4,735 条语言：中文领域：中医药（Traditional Chinese Medicine, TCM）格式：问答对（QA Pair）用途：中医药大模型训练、知识问答系统、语义理解研究
📚 简介
“白泽中医药大模型语料库”是一个专注于中医药领域的高质量问答语料集合，旨在支持中医药知识的数字化、智能化应用。语料库共包含 4,735 条 经过整理与校对的问答对，涵盖中医基础理论、中药学、方剂学、诊断学、针灸推拿、经典医籍、临床实践等多个子领域。
本语料库可广泛应用于：
中医药大语言模型的预训练与微调
智能问答系统开发
医学自然语言处理任务（如实体识别、关系抽取）
中医药知识图谱构建
🧩 数据内容
每条语料为一个标准的问答对，格式如下：
{
"instruction": "广义转录组和狭义转录组在定义上的主要区别是什么？",
"input": "",
"output":… See the full description on the dataset page: https://huggingface.co/datasets/DigitalIntelligenceCenter-of-ICMM/Baize-TCM-Corpus-for-Large-Language-Models-V1.Prompts-for-Large-Language-Model
Development/Learning
This is a Dataset of Prompts for Large Language Model
Large-Language-Models-Often-Know-When-They-Are-Being-Evaluated
Dataset Card for Evaluation Awareness Benchmark
Dataset Summary
This benchmark checks whether a language model can recognise when a conversation is itself part of an evaluation rather than normal, real-world usage. The dataset contains 976 conversational transcripts with rich metadata, including:
True evaluation transcripts from prompt-injection tests, red-teaming tasks, and coding challenges
Organic/real transcripts from actual user queries, scraped chats, and… See the full description on the dataset page: https://huggingface.co/datasets/eval-aware/Large-Language-Models-Often-Know-When-They-Are-Being-Evaluated.wav2vec-large-swahili-asr-model-with-swahili-language-modelwav2vec-large-swahili-asr-model-with-swahili-language-model_Role-of-Provider-on-Safety-Alignment-in-Large-Language-Models
Evaluating the Role of Provider on Safety Alignment in Large Language Models: dataset
Data for the paper
Naser, M.Z. (2026). Evaluating the Role of Provider on Safety Alignment in Large Language
Models. Neurocomputing, 135173. https://doi.org/10.1016/j.neucom.2026.135173
It holds the Extended Context Safety Benchmark (ECSB) scenario bank and every trial result.
If you use the data, please cite the paper (BibTeX under Citation).
The metadata.paper field inside… See the full description on the dataset page: https://huggingface.co/datasets/mznaser/Role-of-Provider-on-Safety-Alignment-in-Large-Language-Models.