datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.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.domain-agnostic-causal-reasoning-tuning
Domain-Agnostic Causal Reasoning Tuning Dataset
Training data for fine-tuning language models on multi-hop document reasoning. Each example is a graded reasoning trace produced by a frontier AI agent solving a procedurally generated challenge from the Botcoin proof-of-inference network.
The traces contain no real domain knowledge. Entities are fictional, numbers are random, and documents are generated deterministically from 128-bit seeds. The reasoning structure is what matters:… See the full description on the dataset page: https://huggingface.co/datasets/botcoinmoney/domain-agnostic-causal-reasoning-tuning.hse-instruction-tuning
SmartQHSE HSE Instruction-Tuning Corpus
Alpaca-style instruction-tuning variant of the SmartQHSE HSE Q&A Corpus.
Each row has the canonical fine-tuning schema:
{
"instruction": "What is OSHA Process Safety Management 1910.119?",
"input": "",
"output": "<authoritative long-form answer with citations>",
"category": "us-osha",
"source_url": "https://www.smartqhse.com/answers/<slug>"
}
Suitable for LoRA / SFT training of HSE-domain LLMs and RAG systems.
Citation (preferred… See the full description on the dataset page: https://huggingface.co/datasets/SmartQHSE/hse-instruction-tuning.ChEMBL_Drug_Instruction_Tuning
Dataset Card for ChEMBL Drug Instruction Tuning
Dataset Summary
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
[More Information Needed]
Dataset Structure
Data Instances
[More Information Needed]
Data Fields
[More Information Needed]
Data Splits
[More Information Needed]… See the full description on the dataset page: https://huggingface.co/datasets/alxfgh/ChEMBL_Drug_Instruction_Tuning.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/CarsonnnNN/TCM-Instruction-Tuning-ShizhenGPT.Visual-Extraction-Tuning-382K
Visual Extraction Tuning 382K
This repository contains the generated visual extraction tuning dataset from the paper Downscaling Intelligence: Exploring Perception and Reasoning Bottlenecks in Small Multimodal Models.
Project page: https://web.stanford.edu/~markendo/projects/downscaling_intelligence
Code: https://github.com/markendo/downscaling_intelligence
Overview
We provide the 382K examples generated using our visual extraction tuning data generation pipeline.… See the full description on the dataset page: https://huggingface.co/datasets/markendo/Visual-Extraction-Tuning-382K.NCD_Instruct-Tuning_Medical_QA_Indonesian
IndoHealth-NLP Vol. 2: NCD Instruct-Tuning Medical QA (Sample)
📁 VIEW & DOWNLOAD SAMPLE FILES HERE
⚠️ DATASET LIMITATION NOTE:
This repository contains a FREE SAMPLE (200 rows) for evaluation purposes. To download the full, production-ready dataset containing 3,497 meticulously curated rows, please visit our official Gumroad page: [https://3929431511879.gumroad.com/l/IndoHealth-NLPVol2NCDInstruct-TuningMedicalQAIndonesian]
Dataset Summary
Building localized… See the full description on the dataset page: https://huggingface.co/datasets/IndoHealth-NLP/NCD_Instruct-Tuning_Medical_QA_Indonesian.medical_instruction_tuningMed_LLaMa3_fine-tuning_dataset
Med-LLaMA3 — Medical Instruction Fine-Tuning Dataset
A large, unified medical instruction-tuning corpus (~1.65 million examples) compiled, cleaned, and
standardized from a diverse set of public medical sources. It is the training corpus used to fine-tune
the Med-LLaMA3 family (LLaMA-3.2 1B/3B and LLaMA-3.1 8B) in the paper “Med-LLaMA3: Advancing Medical
Question-Answering Through Parameter-Efficient Fine-Tuning of Large Language Models” (Applied Sciences,
2026). All sources were… See the full description on the dataset page: https://huggingface.co/datasets/MohamedAhmedAE/Med_LLaMa3_fine-tuning_dataset.Instruction-Tuning-with-GPT-4-RedPajama-Chat
Instruction Tuning with GPT 4 RedPajama-Chat
This dataset has been converted from the Instruction-Tuning-with-GPT-4 dataset for the purpose of fine-tuning the RedPajama-INCITE-Chat-3B-v1 model.
About Instruction-Tuning-with-GPT-4
English Instruction-Following Data generated by GPT-4 using Alpaca prompts for fine-tuning LLMs.
Usage and License Notices
The data is intended and licensed for research use only. The dataset is CC BY NC 4.0 (allowing only… See the full description on the dataset page: https://huggingface.co/datasets/Fredithefish/Instruction-Tuning-with-GPT-4-RedPajama-Chat.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… See the full description on the dataset page: https://huggingface.co/datasets/Soban1234/Trendyol-Cybersecurity-Instruction-Tuning-Dataset.Trendyol-Cybersecurity-Instruction-Tuning-Dataset-archive
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… See the full description on the dataset page: https://huggingface.co/datasets/ChipHolmes/Trendyol-Cybersecurity-Instruction-Tuning-Dataset-archive.snorkel-curated-instruction-tuningPlease check out our Blog Post - How we built a better GenAI with programmatic data development for more details!
Summary
snorkel-curated-instruction-tuning is a curated dataset that consists of high-quality instruction-response pairs.
These pairs were programmatically filtered with weak supervision from open-source datasets Databricks Dolly-15k,
Open Assistant,
and Helpful Instructions.
To enhance the dataset, we also programmatically classified each instruction based on the… See the full description on the dataset page: https://huggingface.co/datasets/snorkelai/snorkel-curated-instruction-tuning.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/ahmadkaab/Trendyol-Cybersecurity-Instruction-Tuning-Dataset.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/andycoco1128/Trendyol-Cybersecurity-Instruction-Tuning-Dataset.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/ukcli/Trendyol-Cybersecurity-Instruction-Tuning-Dataset.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/invinciblejha01/Trendyol-Cybersecurity-Instruction-Tuning-Dataset.High-Quality-Synthetic-Python-Dataset-with-Reasoning-Traces-Chain-of-Thought-for-LLM-Fine-Tuning
PyReason-7k: Advanced Python Chain-of-Thought Dataset
Dataset Description
This dataset contains 7,000+ high-quality Python programming examples designed for LLM fine-tuning.
Each entry includes a detailed thought_process (Chain-of-Thought) to teach models logical reasoning before coding.
Key Features:
Chain-of-Thought: Step-by-step reasoning traces.
Error Handling: Solutions include try-except blocks and logging.
Diverse Tasks: Algorithms, API handling, Data Structures.… See the full description on the dataset page: https://huggingface.co/datasets/xTayyub/High-Quality-Synthetic-Python-Dataset-with-Reasoning-Traces-Chain-of-Thought-for-LLM-Fine-Tuning.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/Madhu348/Trendyol-Cybersecurity-Instruction-Tuning-Dataset.fine-tuning-socratic-dataset
Fine-Tuning Concepts Dataset - Socratic Method
A dataset of 100 conversation pairs teaching fine-tuning concepts through Socratic questioning.
Dataset Summary
Size: 100 conversations
Format: Chat format (system, user, assistant)
Method: Socratic questioning - guides learning through questions rather than direct answers
Topics: Fine-tuning, PEFT methods (LoRA, QLoRA), data quality, troubleshooting
Usage
from datasets import load_dataset
dataset =… See the full description on the dataset page: https://huggingface.co/datasets/sanjaypantdsd/fine-tuning-socratic-dataset.my-recipe-chat-fine-tuning-data
Dataset Card for my-recipe-chat-fine-tuning-data
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/vector124/my-recipe-chat-fine-tuning-data/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info --config… See the full description on the dataset page: https://huggingface.co/datasets/vector124/my-recipe-chat-fine-tuning-data.Trendyol-Cybersecurity-Instruction-Tuning-Dataset-EDIT
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/JEAPI/Trendyol-Cybersecurity-Instruction-Tuning-Dataset-EDIT.Trendyol-Cybersecurity-Instruction-Tuning-Dataset-EDIT
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/invinciblejha01/Trendyol-Cybersecurity-Instruction-Tuning-Dataset-EDIT.mirror-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… See the full description on the dataset page: https://huggingface.co/datasets/alucent/mirror-Trendyol-Cybersecurity-Instruction-Tuning-Dataset.Llama-2-fine-tuning
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/BhaskarAgrawal/Llama-2-fine-tuning.instruction_tuning_datasets
🧠 Persian Cultural Alignment Dataset for LLMs
This repository contains a high-quality, instruction-following dataset for cultural alignment of large language models (LLMs) in the Persian language. The dataset is curated using hybrid strategies that incorporate culturally grounded generation, multi-turn dialogues, translation, and augmentation methods, making it suitable for SFT, DPO, RLHF, and alignment evaluation.
📚 Dataset Overview
Domain
Methods Used… See the full description on the dataset page: https://huggingface.co/datasets/MatinaAI/instruction_tuning_datasets.fine-tuning_dataset
Fine-tuning Dataset
Description
This dataset contains 400 question-answer pairs for fine-tuning language models. Each pair consists of a query and an editor's answer, along with citations for the answer.
Data attributes
The dataset is in a CSV format with the following parameters:
Query (str): The question.
Editor's answer (str): The answer to the question.
Citations (list of str): A list of citations for the answer.
Data Source
The data was… See the full description on the dataset page: https://huggingface.co/datasets/SoftAge-AI/fine-tuning_dataset.fine_tuning_demo_Dataset