datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
python_code_instructions_18k_alpaca
Dataset Card for python_code_instructions_18k_alpaca
The dataset contains problem descriptions and code in python language.
This dataset is taken from sahil2801/code_instructions_120k, which adds a prompt column in alpaca style. Refer to the source here.
code_instructions_120k_alpaca
Dataset Card for code_instructions_120k_alpaca
This dataset is taken from sahil2801/code_instructions_120k, which adds a prompt column in alpaca style. Refer to the original source here.
llava-1.5-665k-instructionsThis dataset repository, LLaVA-1.5-665K-Instructions, is notably utilized in the paper Zero-Shot Vision Encoder Grafting via LLM Surrogates.
The official code repository for the paper can be found here: https://github.com/kaiyuyue/zero
LLaVA-1.5-665K-Instructions
This dataset repo contains the entire LLaVA-1.5-665K-Instructions in one place, including images and text sequences.
The images are in train_split/*.tars and the text sequences are in jsons:
llava_v1_5_mix665k.json is the… See the full description on the dataset page: https://huggingface.co/datasets/kaiyuyue/llava-1.5-665k-instructions.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.star-dataset-instructions
STAR Instructions
STAR Instructions is a large-scale Arabic instruction-tuning dataset built by rendering the 355 STAR Jinja2 prompt templates against their 87 source datasets, covering 27 raw task labels (20 tasks after merging closely related categories, as reported in the paper). The underlying templates were authored collaboratively using PromptLab. This dataset and the experiments built on it are described in STAR: instruction tuning for Arabic across tasks, datasets, and… See the full description on the dataset page: https://huggingface.co/datasets/KFUPM-JRCAI/star-dataset-instructions.paper_instructions_300K-v1Loading will work as follows:
Existing behavior
# Loads the SFT dataset containing instruction, prompt, output
load_dataset("paperbd/paper_instructions_300K-v1")
Reasoning variant
# Loads reasoning subset containing instruction, prompt, reasoning, output
load_dataset(
"paperbd/paper_instructions_300K-v1",
"reasoning",
split="train",
)
Dataset Summary
This dataset contains synthetic supervised fine-tuning data generated from academic… See the full description on the dataset page: https://huggingface.co/datasets/paperbd/paper_instructions_300K-v1.python-code-instructions-japanese
Python Code Instructions - Japanese (18K)
Dataset Description
This dataset contains 18,612 Python programming instruction-response pairs translated to Japanese. It's designed for training language models to understand and generate Python code based on Japanese instructions.
Key Features
18,612 entries covering diverse Python programming tasks
Japanese instructions and prompts for code generation
Original English text preserved for reference
Python code… See the full description on the dataset page: https://huggingface.co/datasets/ronantakizawa/python-code-instructions-japanese.unity-dev-instructions
Unity Developer Instructions
A comprehensive instruction-tuning dataset for Unity game development,
covering C# scripting, XR/VR development, physics, animation, rendering,
UI Toolkit, and performance optimization.
Dataset Summary
Split
Count
Train
46,483
Test
2,446
Total
48,929
Data Sources
| unity_docs | 40,496 |
| stackoverflow | 6,071 |
| github | 2,362 |
Source breakdown:
Source
Count
unity_docs
40,496
stackoverflow
6,071… See the full description on the dataset page: https://huggingface.co/datasets/vishnuOI/unity-dev-instructions.Myanmar-Tuberculosis-Guidelines-Instructions
Myanmar Tuberculosis Guidelines Instructions
A bilingual instructional dataset built to support Myanmar's ongoing fight against tuberculosis — turning life-saving guidelines into a usable resource for healthcare workers, educators, and AI researchers working with low-resource languages.
Authors: Min Si Thu, Khin Myat Noe
Abstract
Tuberculosis is still one of Myanmar's biggest public health problems. Part of the difficulty is that good, standardized TB education… See the full description on the dataset page: https://huggingface.co/datasets/jojo-ai-mst/Myanmar-Tuberculosis-Guidelines-Instructions.tat-llm-instructions
TAT-LLM-Instructions
The TAT(Tabular and Textual)-LLM-Instructions dataset is a curated collection of financial data, structured to resemble instructions. It aggregates information from three publicly available tabular and textual QA datasets: FinQA, TAT-QA, and TAT-DQA. By employing specialized templates, TAT-LLM-Instructions transforms the original dataset into prompts that are optimized for compatibility with large language models (LLMs) and external executor, aiming to… See the full description on the dataset page: https://huggingface.co/datasets/next-tat/tat-llm-instructions.russian-easy-instructions
Easy Russian Instructions
Fast instructions in conversational format, generaly used for injecting general knowledge.Dataset contains comprehensive instructions for easy tasks and general question answering
Contents:
Wikipedia / Factological knowledge
History knowledge
Basic programming understanding
Basic math understanding
Basic physics understanding
Basic geography knowledge
Basic biology knowledge
Format:
Formatted for instruction-tuning / instruction… See the full description on the dataset page: https://huggingface.co/datasets/attn-signs/russian-easy-instructions.ALIA-es-biomedical-synthetic-instructions
Dataset Introduction
The ALIA Spanish Biomedical Synthetic Instructions Corpus is a synthetic instruction-tuning resource in Spanish created under the ALIA project using the Magpie methodology. It was designed to train and evaluate language models in biomedical and healthcare tasks with controlled formats and large-scale supervision.
It contains:
639,456 instances
961,073,205 tokens
14 task modalities (clinical diagnosis, patient education, ethical reasoning, document… See the full description on the dataset page: https://huggingface.co/datasets/SINAI/ALIA-es-biomedical-synthetic-instructions.ALIA-es-legal-administrative-synthetic-instructions
Dataset Introduction
The ALIA Spanish Legal and Administrative Synthetic Instructions Corpus is a synthetic instruction-tuning resource in Spanish created under the ALIA project using the Magpie methodology. It was designed to train and evaluate language models in legal and administrative tasks with controlled formats and large-scale supervision.
It contains:
763,804 instances
534,112,398 tokens
16 task modalities (questions, instructions, multiple-choice, true/false; with and… See the full description on the dataset page: https://huggingface.co/datasets/SINAI/ALIA-es-legal-administrative-synthetic-instructions.synthea-ncd-instructions
Synthea NCD Instructions
Synthetic EHR-based instruction-tuning dataset for training LLMs to predict non-communicable disease (NCD) risk, specifically Type 2 Diabetes and Hypertension.
Quick Start
from datasets import load_dataset
dataset = load_dataset("samwell/synthea-ncd-instructions")
# View a sample
print(dataset["train"][0])
Dataset Description
This dataset contains instruction-tuning examples derived from synthetic patient records generated using… See the full description on the dataset page: https://huggingface.co/datasets/samwell/synthea-ncd-instructions.idirak-uyghur-instructions
IDIRAK Uyghur Instructions
A conversational dataset for developing and evaluating the IDIRAK Uyghur AI
assistant. Rows use Hugging Face's messages format and include provenance,
category, license, and review status fields.
Important status
This version contains 50 schema and pipeline seed examples across training,
validation, and test splits. It is not large enough to produce a strong model.
Every included row is marked needs_native_review and must be checked by a… See the full description on the dataset page: https://huggingface.co/datasets/UyghurAI/idirak-uyghur-instructions.ALIA-es-cultural-heritage-synthetic-instructions
Dataset Introduction
The ALIA Spanish Cultural and Heritage Synthetic Instructions Corpus is a synthetic instruction-tuning resource in Spanish created under the ALIA project using the Magpie methodology. It was designed to train and evaluate language models in cultural heritage, digital humanities, and historical knowledge tasks with natural linguistic variation and large-scale supervision.
It contains:
748,480 instances
629,682,398 tokens
25 task modalities (heritage QA… See the full description on the dataset page: https://huggingface.co/datasets/SINAI/ALIA-es-cultural-heritage-synthetic-instructions.cybersecurity-controls-instructions
Cybersecurity Controls Instructions
Security control, incident response and risk management guidance from NIST Special Publications, turned into instruction-following examples.
Splits
split
rows
source documents
train
13,106
56
validation
4,840
18
test
5,697
18
Splits are held out by source document. Every chunk yields several
instruction rows, so a random row-level split would place the same passage in
train and test; whole documents are held… See the full description on the dataset page: https://huggingface.co/datasets/nuhmanpk/cybersecurity-controls-instructions.Privacy-Expert-Instructions
Dataset Card: Privacy-Expert-Instructions
This dataset contains 13000+ high-quality instruction-tuning pairs focused on Privacy and Data Protection. The data was curated from several StackExchange communities (Security, SuperUser, StackOverflow, etc.) and processed into a clean Alpacca-style format.
Dataset Summary
The primary goal of this dataset is to provide fine-tuning data for LLMs to understand and answer questions regarding:
Online Privacy: Tracking, anonymity… See the full description on the dataset page: https://huggingface.co/datasets/meeAtif/Privacy-Expert-Instructions.emergency-response-instructions
Emergency Response Instructions
A supervised fine-tuning (SFT) dataset built from official government and international organization documents focused on disaster preparedness, emergency response, and crisis safety.
The dataset consolidates trusted guidance from agencies like FEMA, CDC, USGS, DHS, WHO, IFRC, UNICEF, Red Cross, and more — transforming them into structured instruction-following examples.
Coverage
This dataset spans multi-hazard scenarios, including:… See the full description on the dataset page: https://huggingface.co/datasets/nuhmanpk/emergency-response-instructions.cantonese-qa-instructions
🇭🇰 Cantonese QA Instructions (v0.3)
粵語 / 廣東話指令微調數據集 — 全合成、全 QC'd、全繁體中文輸出
A high-quality synthetic instruction-tuning dataset of natural spoken Cantonese queries paired with Traditional Chinese answers (50–200 characters). Covers 6 diverse domains at varying difficulty levels. Generated by Qwen 3.6 Dense and quality-controlled by DeepSeek V4 Pro. Fully automated nightly generation pipeline on dedicated hardware.
🔗 View on Hugging Face
📊 Dataset Stats (v0.3)… See the full description on the dataset page: https://huggingface.co/datasets/him0413/cantonese-qa-instructions.smart-contracts-instructions
Smart Contracts Instructions
A dataset containing 6,003 GPT-generated human instruction and Solidity source code data pairs.
GPT models used to make this data are GPT-3.5 turbo, GPT-3.5 turbo 16k context, and GPT-4. Solidity source codes are used from mwritescode's Slither Audited Smart Contracts (https://huggingface.co/datasets/mwritescode/slither-audited-smart-contracts).
Distributions of the GPT models used to make this dataset:
GPT-3.5 Turbo: 5,276
GPT-3.5 Turbo 16k Context:… See the full description on the dataset page: https://huggingface.co/datasets/AlfredPros/smart-contracts-instructions.collected-turkish-instructions-v0.1This dataset is the result of merging and cleaning data from the following sources:
Turkish Poems Cleaned
Turkish Reading Comprehension Question Answering Dataset
Stanford ALPaCA Cleaned Turkish Translated
Turkish Poems
Turkish Folk Song Lyrics
The data has been merged and processed for quality and consistency to create this dataset.
sequential-instructions
Sequential Instructions
This is the sequential instructions dataset from Understanding the Effects of RLHF on LLM Generalisation and Diversity. The dataset is in the alpaca_eval format.
For information about how the dataset was generated, see https://github.com/RobertKirk/stanford_alpaca.
The instructions in the dataset generally have a sequence of steps we expect the model to complete all at once. In our work, we found that RLHF models generalise much better to this dataset than… See the full description on the dataset page: https://huggingface.co/datasets/UCL-DARK/sequential-instructions.instruction_set_hindi_1035The dataset has been created using OliveFarm web application.
Following domains have been covered in this dataset:-
Art
Sports (Cricket, Football, Olympics)
Politics
History
Cooking
Environment
Music
Contributors: -
Shahid
Parul.
security-instructions
Security Insutrctions 2.5K
A set of Cybersecurity questions pertaining to different areas of security.
python_code_instructions_18k_alpaca
Dataset Card for python_code_instructions_18k_alpaca
The dataset contains problem descriptions and code in python language.
This dataset is taken from sahil2801/code_instructions_120k, which adds a prompt column in alpaca style. Refer to the source here.
banglabridge-instructions
Dataset Card — BanglaBridge Banglish Instruction Set
Summary
An original instruction-tuning dataset for code-mixed / romanized Bengali
("Banglish") — the register 100M+ people actually type online
(e.g. "kal ki plan? ami free achi"). Every pair is authored by us or produced by
safe, deterministic transformation of our own templates. Nothing is scraped, so the
whole set is free to redistribute on Hugging Face and Kaggle.
This is the originality +… See the full description on the dataset page: https://huggingface.co/datasets/subhajitmahata84/banglabridge-instructions.scidcc-instructions
Dataset Summary
Instruction-Response pairs generated using the SciDCC Climate Dataset from Climabench
Format
### Instruction:
Present a fitting title for the provided text.
For those who study earthquakes, one major challenge has been trying to understand all the physics of a fault -- both during an earthquake and at times of "rest" -- in order to know more about how a particular region may behave in the future. Now, researchers at the California Institute of Technology… See the full description on the dataset page: https://huggingface.co/datasets/tanmaylaud/scidcc-instructions.grade-school-math-instructions-Malagasy
Overview
This dataset is a Malagasy adaptation of grade-school-math-instructions.
It consists of arithmetic word problems converted into instruction-answer pairs in Malagasy.
Each entry contains a math problem presented as an instruction, optional contextual input,
and a detailed step-by-step solution in Malagasy.
The dataset is particularly useful for training and evaluating models on arithmetic reasoning and instruction-following tasks in Malagasy, a low-resource language.… See the full description on the dataset page: https://huggingface.co/datasets/Lo-Renz-O/grade-school-math-instructions-Malagasy.wori-wolof-instructions
WORI — Wolof Reverse Instruction Dataset
WORI (Wolof Reverse Instruction) is a linguistically validated
instruction-tuning dataset for Wolof, a low-resource language.
The dataset provides 3,724 unique instruction-output pairs in Wolof,
with parallel French translations. It was constructed via a reverse instruction
pipeline and validated through a combination of automated language identification
and manual review.
For full methodological details, please refer to the… See the full description on the dataset page: https://huggingface.co/datasets/m-a-d-i/wori-wolof-instructions.