datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Magicoder-OSS-Instruct-75KThis is the OSS-Instruct dataset generated by gpt-3.5-turbo-1106 developed by OpenAI. Please pay attention to OpenAI's usage policy when adopting this dataset: https://openai.com/policies/usage-policies.
Magicoder-Evol-Instruct-110KA decontaminated version of evol-codealpaca-v1. Decontamination is done in the same way as StarCoder (bigcode decontamination process).
InstructCoder
Paper |
Code |
Blog
InstructCoder (CodeInstruct): Empowering Language Models to Edit Code
Updates
May 23, 2023: Paper, code and data released.
Overview
InstructCoder is the first dataset designed to adapt LLMs for general code editing. It consists of 114,239 instruction-input-output triplets and covers multiple distinct code editing scenarios, generated by ChatGPT. LLaMA-33B finetuned on InstructCoder performs on par with ChatGPT on a… See the full description on the dataset page: https://huggingface.co/datasets/likaixin/InstructCoder.Nemotron-SFT-Instruction-Following-Chat-v3
Dataset Description:
The Nemotron-Instruction-Following-Chat-v3 dataset is designed to strengthen multi-turn, interactive capabilities, including open-ended chat and precise instruction following.
The chat subset uses human written prompts from sources like lmarena, lmsys, and wildchat as seed prompts. Responses are generated with GLM-5. Multiple responses are sampled from the model and the best response as judged by pairwise comparisons using Qwen3-Nemotron-235B-A22B-GenRM-2603… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-SFT-Instruction-Following-Chat-v3.Trendyol-Cybersecurity-Instruction-Tuning-Dataset
Trendyol Cybersecurity Defense Instruction-Tuning Dataset (v2.0)
🚀 TL;DR
53,202 meticulously curated system/user/assistant instruction-tuning examples covering 200+ specialized cybersecurity domains. Built by the Trendyol Security Team for training state-of-the-art defensive security AI assistants. Expanded from 21K to 53K rows with comprehensive coverage of modern security challenges including cloud-native threats, AI/ML security, quantum computing risks… See the full description on the dataset page: https://huggingface.co/datasets/Trendyol/Trendyol-Cybersecurity-Instruction-Tuning-Dataset.Malay-Dialect-Instructions
Malay dialect instruction including coding
Negeri Sembilan
QA
public transport QA,
Coding
CUDA coding,
Kedah
QA
infra QA,
Coding
Rust coding,
Kelantan
QA
Najib Razak QA,
Coding
Go coding,
Perak
QA
Anwar Ibrahim QA,
Coding
SQL coding,
Pahang
QA
Pendatang asing QA,
Coding
Typescript coding,
Terengganu… See the full description on the dataset page: https://huggingface.co/datasets/mesolitica/Malay-Dialect-Instructions.mix-instruct
MixInstruct
Introduction
This is the official realease of dataset MixInstruct for project LLM-Blender.
This dataset contains 11 responses from the current popular instruction following-LLMs that includes:
Stanford Alpaca
FastChat Vicuna
Dolly V2
StableLM
Open Assistant
Koala
Baize
Flan-T5
ChatGLM
MOSS
Moasic MPT
We evaluate each response with auto metrics including BLEU, ROUGE, BERTScore, BARTScore. And provide pairwise comparison results by prompting ChatGPT for the… See the full description on the dataset page: https://huggingface.co/datasets/llm-blender/mix-instruct.pmc_llama_instructionsThis repo provides part of the dataset used for PMC-LLaMA-13B's instruction tuning.
Data
Size
Link
ChatDoctor
100K
https://www.yunxiangli.top/ChatDoctor/
MedQA
10.2K
https://huggingface.co/datasets/GBaker/MedQA-USMLE-4-options
MedMCQA
183K
https://huggingface.co/datasets/medmcqa
PubmedQA
211K
https://huggingface.co/datasets/pubmed_qa
LiveQA
635
https://huggingface.co/datasets/truehealth/liveqa
MedicationQA
690
https://huggingface.co/datasets/truehealth/medicationqa
UMLS… See the full description on the dataset page: https://huggingface.co/datasets/axiong/pmc_llama_instructions.McEval-InstructMcEval-Instruct data as described in the McEval Paper. Code for the evaluation and sft can be found on Github as McEval.
TCM-Instruction-Tuning-ShizhenGPT
📚 Introduction
This dataset is a fine-tuning dataset for ShizhenGPT, a multimodal LLM for Traditional Chinese Medicine (TCM). We open-source 245K multimodal Chinese medicine instruction data, including text instructions, visual instructions, and signal instructions for TCM.
For details, see our paper and GitHub repository.
📊 Dataset Overview
The open-sourced fine-tuning dataset consists of three parts:
Modality
Data Quantity
TCM Text Instructions
📝 Text… See the full description on the dataset page: https://huggingface.co/datasets/FreedomIntelligence/TCM-Instruction-Tuning-ShizhenGPT.cpt_instruction_datasets
Instruction datasets
Collection of synthetic instruction datasets used during the continued pretraining of Model-small-instr-1, Model-small-instr-2 and Model-small-instr-3. You can currently find these models under: Llama-3.1-Carballo-Instr1 and Llama-3.1-Carballo-Instr3.
Dataset creation
Datasets were created using two different techniques:
Adapting already existing datasets or corpora by modifying their format to make them suitable for including instructions during… See the full description on the dataset page: https://huggingface.co/datasets/proxectonos/cpt_instruction_datasets.law-instructions-dataset
Nepali Source-Grounded Instruction Dataset
Synthetic Nepali instruction-tuning data generated with NVIDIA NeMo Data
Designer from authoritative Nepali documents (agriculture manuals, legal
texts). Answers are grounded strictly in the source; unanswerable questions
get an explicit refusal. Records use chat messages format plus metadata
and per-record quality_scores (grounding / correctness / naturalness, 1-5,
LLM-as-judge). One data/train-<shard>.jsonl per source document; shards… See the full description on the dataset page: https://huggingface.co/datasets/aarajbhattarai/law-instructions-dataset.Chinese-Instruct
中文指令微调数据集
💻 Github Repo
本项目旨在构建一个高质量、多领域、大规模的中文指令微调数据集。
本项目将会持续更新。更多数据集欢迎访问 Github Repo。
[!TIP]
如果您想要一个可用于学习的简化版中文指令数据集，可以访问：Mxode/Chinese-Instruct-Lite
具体构成
dpsk-r1-distil：中文 DeepSeek-R1 蒸馏数据集，来自 Congliu/Chinese-DeepSeek-R1-Distill-data-110k，根据打分质量做了筛选，提取了最终的回答，未包含思考过程。
chinese-reasoning-distil：中文推理蒸馏数据集，来自 Mxode/Chinese-Reasoning-Distil-Data，提取了最终的回答，未包含思考过程。
firefly：中文通用指令微调数据集，指令取自 Mxode/Firefly-1.1M-Rephrased，其本身已经相较于原 Firefly… See the full description on the dataset page: https://huggingface.co/datasets/Mxode/Chinese-Instruct.bash-instruct-III-55k
Bash Instruct III — 54,360 verified natural-language → Bash pairs
Bash Instruct III is a synthetic instruction-tuning dataset that maps natural-language
requests to correct Bash: single commands, short pipelines, and multi-line scripts. It
is built for supervised fine-tuning of small and mid-size LLMs that must turn a plain
request into shell code that actually runs.
Every row is a three-turn chat conversation (system / user / assistant) with metadata
for slicing (category… See the full description on the dataset page: https://huggingface.co/datasets/Frost2o24/bash-instruct-III-55k.ds-coder-instruct-v1
Dataset Card for DS Coder Instruct Dataset
DS Coder is a dataset for instruction fine tuning of language models. It is a specialized dataset focusing only on
data science (eg. plotting, data wrangling, machine learnig models, deep learning, and numerical computations). The dataset contains code examples both in R and Python.
The goal of this dataset is to enable creation of small-scale, specialized language model assistants for data science projects.
Dataset Details… See the full description on the dataset page: https://huggingface.co/datasets/ed001/ds-coder-instruct-v1.Nemotron-RL-Instruction-Following-Free-Form-Formatting-v1
Dataset Description:
Teaches the model to follow arbitrary text formatting instructions (bullet styles, numbering, delimiters, heading formats, inline emphasis, web-answer structure, etc.) for targeted chat behaviors. Uses explicit Regex and string matching for the reward signal.
This dataset is ready for commercial or non-commercial uses.
Dataset Owner(s):
NVIDIA Corporation
Dataset Creation Date:
Created on: April 10, 2026
Last Modified on: April… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-RL-Instruction-Following-Free-Form-Formatting-v1.RAG-Instruct
Introduction
RAG-Instruct is a RAG dataset designed to comprehensively enhance LLM RAG capabilities, synthesized using GPT-4o. This dataset is based on the Wikipedia corpus and This dataset is based on the Wikipedia corpus and offers the advantages of query-document scenario diversity and task diversity.
The RAG-Instruct dataset can significantly enhance the RAG ability of LLMs and make remarkable improvements in RAG performance across various tasks.
Model
WQA (acc)
PQA (acc)… See the full description on the dataset page: https://huggingface.co/datasets/FreedomIntelligence/RAG-Instruct.Wizard-LM-Chinese-instruct-evolWizard-LM-Chinese是在MSRA的Wizard-LM数据集上，对指令进行翻译，然后再调用GPT获得答案的数据集
Wizard-LM包含了很多难度超过Alpaca的指令。
中文的问题翻译会有少量指令注入导致翻译失败的情况
中文回答是根据中文问题再进行问询得到的。
我们会陆续将更多数据集发布到hf，包括
Coco Caption的中文翻译
CoQA的中文翻译
CNewSum的Embedding数据
增广的开放QA数据
WizardLM的中文翻译
如果你也在做这些数据集的筹备，欢迎来联系我们，避免重复花钱。
骆驼(Luotuo): 开源中文大语言模型
https://github.com/LC1332/Luotuo-Chinese-LLM
骆驼(Luotuo)项目是由冷子昂 @ 商汤科技, 陈启源 @ 华中师范大学 以及 李鲁鲁 @ 商汤科技 发起的中文大语言模型开源项目，包含了一系列语言模型。
( 注意: 陈启源 正在寻找2024推免导师，欢迎联系 )
骆驼项目不是商汤科技的官方产品。
Citation… See the full description on the dataset page: https://huggingface.co/datasets/silk-road/Wizard-LM-Chinese-instruct-evol.INSTRUCT_JEV
INSTRUCT_JEV
INSTRUCT_JEV is an instruction corpus built from the TypeSafe AI documentation
for Jev, the first System One model. It is structured around the three TypeSafe
question primitives - Choice, Noul and Score - and mirrors the raw corpus
captured in deckerGUI-jev_corpus_RAW.
Credits
INSTRUCT_JEV is a DeckerGUI project and exists because of the work below.
Who
Contribution
Link
TypeSafe AI
Jev - the first System One model - and the Choice / Noul… See the full description on the dataset page: https://huggingface.co/datasets/ctaxnagomi/INSTRUCT_JEV.Nemotron-RL-Instruction-Following-Citation-Formatting-v1
Dataset Description:
Teaches the model to cite specific document parts using reference markers like [ref:1], ref:3, etc. Supports single-reference, multi-reference, and inline citations.
This dataset is ready for commercial/non-commercial uses.
Dataset Owner(s):
NVIDIA Corporation
Dataset Creation Date:
Created on: April 10, 2026
Last Modified on: April 10, 2026
Version:
Nemotron-RL-Instruction-Following-CitationFormatting-v1… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-RL-Instruction-Following-Citation-Formatting-v1.rombodawg-Everything_Instruct
Everything-Instruct: Supervised Finetuning Dataset
This dataset contains over 7 000 000 instruction-response pairs for supervised fine-tuning large language models.
It combines the following datasets:
rombodawg/Everything_Instruct
rombodawg/Everything_Instruct_Multilingual
It can be used for:
Improving code generation and debugging
Enhancing creative writing
Improving general instruction followingFor English and many other languages
Processing
Removing duplicate… See the full description on the dataset page: https://huggingface.co/datasets/agentlans/rombodawg-Everything_Instruct.InstrucTurca
InstrucTurca v1.0.0 is a diverse synthetic instruction tuning dataset crafted for instruction-tuning Turkish LLMs. The data is compiled data various English datasets and sources, such as code instructions, poems, summarized texts, medical texts, and more.
Dataset content
BI55/MedText
checkai/instruction-poems
garage-bAInd/Open-Platypus
Locutusque/ColumnedChatCombined
nampdn-ai/tiny-codes
Open-Orca/OpenOrca
pubmed_qa
TIGER-Lab/MathInstruct… See the full description on the dataset page: https://huggingface.co/datasets/turkish-nlp-suite/InstrucTurca.python-code-instructions-85k
Python Code Instructions - 85K
Instruction-tuning dataset of Python functions paired with short natural-language instructions derived from repository docstrings.
What changed in this release
This release keeps the original public rows and format, but makes the dataset easier to use responsibly:
exact duplicate rows were removed again using normalized instruction + output hashing
deterministic train, validation, and test splits were added
the dataset card now documents… See the full description on the dataset page: https://huggingface.co/datasets/NickIBrody/python-code-instructions-85k.russian_instructions_2_cleaned
Russian Instructions Cleaned
Очищенная версия Den4ikAI/russian_instructions_2.
Что сделано
Дедупликация по question (удалено ~45k)
Удалены пустые question и answer
Удалены ответы короче 100 и длиннее 4000 символов
Конвертировано в chat-формат (messages: user/assistant)
Статистика
Метрика
Значение
Исходно
237 281
После чистки
138 973
Удалено
98 308 (41%)
Формат
JSONL, одна строка = один пример.
{"messages":… See the full description on the dataset page: https://huggingface.co/datasets/Lev384501/russian_instructions_2_cleaned.ds-coder-instruct-v2
Dataset Card for DS Coder Instruct v2 Dataset
Changes from v1:
Added WizardLM evol data science samples
Removed R samples from v2
DS Coder is a dataset for instruction fine tuning of language models. It is a specialized dataset focusing only on
data science (eg. plotting, data wrangling, machine learnig models, deep learning, and numerical computations). The dataset contains code examples both in Python (R samples were removed in v2).
The goal of this dataset is to enable… See the full description on the dataset page: https://huggingface.co/datasets/ed001/ds-coder-instruct-v2.dfm13-multilingual-grounded-instruct-hu
dfm13_wave4_synthetic_hu_grounded_instruct
20000 complete conversations; 20000 native assistant targets. All user/tool history and tool definitions are preserved. Gemma native student rendering, thinking disabled. Generated and separately model-reviewed by Gemma4 26B A4B; automated judgments are fallible, not human or native-speaker certification.
Includes unchanged original accepted conversations and narrowly recovered complete keep reviews rejected solely for an empty… See the full description on the dataset page: https://huggingface.co/datasets/schneiderkamplab/dfm13-multilingual-grounded-instruct-hu.dfm13-multilingual-grounded-instruct-bg
dfm13_wave4_synthetic_bg_grounded_instruct
20000 complete conversations; 20000 native assistant targets. All user/tool history and tool definitions are preserved. Gemma native student rendering, thinking disabled. Generated and separately model-reviewed by Gemma4 26B A4B; automated judgments are fallible, not human or native-speaker certification.
Includes unchanged original accepted conversations and narrowly recovered complete keep reviews rejected solely for an empty… See the full description on the dataset page: https://huggingface.co/datasets/schneiderkamplab/dfm13-multilingual-grounded-instruct-bg.Magicoder-OSS-Instruct-Rust-cleaned-3.9K
🦀 Magicoder-OSS-Instruct-Rust (3.9K Cleaned)
Magicoder-OSS-Instruct-Rust is a high-quality, syntax-verified dataset of 3,909 Rust coding instructions derived from real-world open-source GitHub projects.
This dataset is extracted from ise-uiuc/Magicoder-OSS-Instruct-75K, filtered specifically for Rust, and validated via in-memory compiler checks. No language translation was applied; the dataset remains in its original English format.
⚙️ Filtering and Verification… See the full description on the dataset page: https://huggingface.co/datasets/WrittenWithRust/Magicoder-OSS-Instruct-Rust-cleaned-3.9K.dfm13-multilingual-grounded-instruct-sk
dfm13_wave4_synthetic_sk_grounded_instruct
20000 complete conversations; 20000 native assistant targets. All user/tool history and tool definitions are preserved. Gemma native student rendering, thinking disabled. Generated and separately model-reviewed by Gemma4 26B A4B; automated judgments are fallible, not human or native-speaker certification.
Includes unchanged original accepted conversations and narrowly recovered complete keep reviews rejected solely for an empty… See the full description on the dataset page: https://huggingface.co/datasets/schneiderkamplab/dfm13-multilingual-grounded-instruct-sk.dfm13-multilingual-grounded-instruct-sl
dfm13_wave4_synthetic_sl_grounded_instruct
20000 complete conversations; 20000 native assistant targets. All user/tool history and tool definitions are preserved. Gemma native student rendering, thinking disabled. Generated and separately model-reviewed by Gemma4 26B A4B; automated judgments are fallible, not human or native-speaker certification.
Includes unchanged original accepted conversations and narrowly recovered complete keep reviews rejected solely for an empty… See the full description on the dataset page: https://huggingface.co/datasets/schneiderkamplab/dfm13-multilingual-grounded-instruct-sl.