datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
gpqa
Dataset Card for GPQA
GPQA is a multiple-choice, Q&A dataset of very hard questions written and validated by experts in biology, physics, and chemistry. When attempting questions out of their own domain (e.g., a physicist answers a chemistry question), these experts get only 34% accuracy, despite spending >30m with full access to Google.
We request that you do not reveal examples from this dataset in plain text or images online, to reduce the risk of leakage into foundation… See the full description on the dataset page: https://huggingface.co/datasets/Idavidrein/gpqa.Tunisian-Proverbs-with-Image-Associations-A-Cultural-and-Linguistic-DatasetTunisian Proverbs with Image Associations: A Cultural and Linguistic Dataset
Description
This dataset explores the rich oral tradition of Tunisian proverbs mapped into text format, pairing each with contextual explanations, English translations both word-to-word and it's equivalent Target Language dynamic, Automated prompt and AI-generated visual interpretations.
It bridges linguistic, cultural, and visual modalities making it valuable for tasks in cross-cultural NLP, generative… See the full description on the dataset page: https://huggingface.co/datasets/HabibaAbderrahim/Tunisian-Proverbs-with-Image-Associations-A-Cultural-and-Linguistic-Dataset.ICPC_Data
ICPC World Finals — a discriminative subset, with model traces
24 ICPC World Finals problems (2021–2025), together with the full transcripts of an
LLM attempting each of them three times under simulated contest rules.
Selection
The model
Every run in this dataset comes from:
nvidia/Nemotron-Cascade-2-30B-A3B
The partitions
Every one of the 53 problems was run 3 times (seeds 1, 2, 3). Each problem was then
placed by its pass rate and… See the full description on the dataset page: https://huggingface.co/datasets/xupy21/ICPC_Data.Sujet-Finance-Instruct-177k
Sujet Finance Dataset Overview
The Sujet Finance dataset is a comprehensive collection designed for the fine-tuning of Language Learning Models (LLMs) for specialized tasks in the financial sector. It amalgamates data from 18 distinct datasets hosted on HuggingFace, resulting in a rich repository of 177,597 entries. These entries span across seven key financial LLM tasks, making Sujet Finance a versatile tool for developing and enhancing financial applications of AI.… See the full description on the dataset page: https://huggingface.co/datasets/sujet-ai/Sujet-Finance-Instruct-177k.misconceptionsEthical-Reasoning-in-Mental-Health-v1This repository contains the dataset for the paper EthicsMH: A Pilot Benchmark for Ethical Reasoning in Mental Health AI.
Overview
Ethical-Reasoning-in-Mental-Health-v1 (EthicsMH) is a carefully curated dataset focused on ethical decision-making scenarios in mental health contexts.This dataset captures the complexity of real-world dilemmas faced by therapists, psychiatrists, and AI systems when navigating critical issues such as confidentiality, autonomy, and bias.
Each sample… See the full description on the dataset page: https://huggingface.co/datasets/UVSKKR/Ethical-Reasoning-in-Mental-Health-v1.iac-eval
IaC-Eval dataset (v1.1)
IaC-Eval dataset is the first human-curated and challenging Cloud Infrastructure-as-Code (IaC) dataset tailored to more rigorously benchmark large language models' IaC code generation capabilities.
This dataset contains 458 questions ranging from simple to difficult across various cloud services (targeting AWS for now).
| Github | 🏆 Leaderboard TBD | 📖 NeurIPS 2024 Paper |
2. Usage instructions
Option 1: Running the evaluation… See the full description on the dataset page: https://huggingface.co/datasets/autoiac-project/iac-eval.AttaQ
AttaQ Dataset Card
The AttaQ red teaming dataset, consisting of 1402 carefully crafted adversarial questions, is designed to evaluate Large Language Models (LLMs) by assessing their tendency to generate harmful or undesirable responses.
It may serve as a benchmark to assess the potential harm of responses produced by LLMs.
The dataset is categorized into seven distinct classes of questions: deception, discrimination, harmful information, substance abuse, sexual content, personally… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/AttaQ.scipar_parallel_docs
SciPar Parallel Documents
Dataset Description
This dataset contains parallel documents (i.e., titles & abstracts) extracted from academic theses, dissertations, and other scientific texts.
In the original paper, we've extracted 9.17M sentence pairs in 31 language pairs from 86 repositories.
This version has been created through further processing and filtering to extract parallel documents instead of parallel sentences.
To do this, we kept only the parallel titles and… See the full description on the dataset page: https://huggingface.co/datasets/ilsp/scipar_parallel_docs.IndicSafe
IndicSafe
Authors: Priyaranjan Pattnayak, Garima Panwar, and Sanchari Chowdhuri.
IndicSafe is a multilingual benchmark for evaluating large-language-model safety behavior across 12 South Asian languages. It contains 6,000 translated prompt rows: 500 source rows in each language, spanning harmful, harmless-control, and deliberately ambiguous categories.
Content warning: the benchmark contains prompts about hate, discrimination, violence, misinformation, political manipulation… See the full description on the dataset page: https://huggingface.co/datasets/ppattnay/IndicSafe.IndustryBench
IndustryBench: Probing the Industrial Knowledge Boundaries of LLMs
💻Github | 📝Paper
IndustryBench is a multi-lingual benchmark for evaluating the industrial domain knowledge of large language models. It comprises 2,049 expert-curated QA pairs spanning 12 industrial sectors, with human-reviewed translations in Chinese, English, Russian, and Vietnamese.
Overview
Dimension
Details
Total questions
2,049
Languages
Chinese (zh), English (en), Russian (ru)… See the full description on the dataset page: https://huggingface.co/datasets/alibaba-multimodal-industrial-ai/IndustryBench.social-instagram-marketing
Social — Instagram Marketing Multimodal Dataset
A synthetic, multimodal dataset for Social, an AI Instagram-marketing agent. Every row is a single Instagram post idea that pairs a marketing caption with a matching AI-generated image, conditioned on a business brief and brand preferences.
Agent pattern: owner brief + brand preferences → 3 similar successful posts (retrieval / recommendation) + 1 freshly generated post (caption + image).
Rows (total)
1,447… See the full description on the dataset page: https://huggingface.co/datasets/avihayamor/social-instagram-marketing.GPT-wiki-intro
GPT Wiki Intro
Overview
Dataset for training models to classify human written vs GPT/ChatGPT generated text.
This dataset contains Wikipedia introductions and GPT (Curie) generated introductions for 150k topics.
Prompt used for generating text
200 word wikipedia style introduction on '{title}'
{starter_text}
where title is the title for the wikipedia page, and starter_text is the first seven words of the wikipedia introduction.
Here's an example of prompt used to… See the full description on the dataset page: https://huggingface.co/datasets/aadityaubhat/GPT-wiki-intro.photonic-integrated-circuit-yield
🏭 Photonic Integrated Circuit Yield Dataset
📊 125,000 synthetic (yield query, yield reasoning response) pairs covering process variation, defect density, lithography, and metrology challenges in CMOS-compatible photonic integrated circuit (PIC) manufacturing.
⚠️ Disclaimer: All entries are synthetically generated. Yield figures are computed from textbook models over sampled inputs, and citations are placeholders styled after technical sources; none reference a real… See the full description on the dataset page: https://huggingface.co/datasets/Taylor658/photonic-integrated-circuit-yield.evalita2026
This repository contains the data release for the Cruciverb-IT shared task on automatic crossword solving in Italian, as part of the 2026 EVALITA campaign. Refer to the task website for more details.
The data from both tasks can be downloaded from the 'Files and versions' tab.
Updates:
Minor update to both task_*_scorer.py in order to convert accented letters to their non-accented counterpart during evaluation
Test data is out!!
The test data of both… See the full description on the dataset page: https://huggingface.co/datasets/cruciverb-it/evalita2026.ivypanda-llm-generated-essays
AI-Generated Essays Dataset
This dataset contains AI-generated academic essays created using the models:
Mistral 7B Instruct v0.2 (Q5_K_M quantized)
Temperature: 0.7
Max tokens: 4096
Top-p: 0.9 (default)
Top-k: 40 (default)
Repeat penalty: 1.1 (default)
Context window: 32768 tokens
Llama 3 13B Instruct v0.1 (Q5_K_M quantized)
Temperature: 0.7
Max tokens: 4096
Top-p: 0.9 (default)
Top-k: 40 (default)
Repeat penalty: 1.1 (default)
Context window: 8192 tokens
DeepSeek-V3.2
API… See the full description on the dataset page: https://huggingface.co/datasets/artfultom/ivypanda-llm-generated-essays.InterviewForge_GenDS
Synthetic Data Generation
Model & Infrastructure
The dataset was generated using the mistral:latest Large Language Model running locally via the Ollama framework. This model was explicitly selected because it balances advanced reasoning capabilities with hardware efficiency, allowing the execution of 10,944 complex generation requests entirely locally on an RTX 3080 GPU without incurring API costs. Additionally, Mistral demonstrated exceptional reliability in… See the full description on the dataset page: https://huggingface.co/datasets/Davichick/InterviewForge_GenDS.IMDb-Media
Dataset Card for "BrightData/IMDb-Media"
Dataset Summary
Explore feature films, TV series, episodes, mini-series, documentaries, and more with this IMDb dataset, comprising over 249K structured records and 32 data fields updated and refreshed regularly.
Each entry includes all major data points such as timestamp, title, URLs, release date, IMDb rating, reviews, awards, origin, category/genre, budget, cast, director, images, videos and more.
For a complete list of data… See the full description on the dataset page: https://huggingface.co/datasets/BrightData/IMDb-Media.engsaf
Engineering Short Answer Feedback
A collection of real short-answer responses from engineering exams across multiple engineering domains.
Background
In recent years, there has been a growing interest in using Artificial Intelligence (AI) to automate student assessment in education.
Among different types of assessments, summative assessments play a crucial role in evaluating a student's understanding level of a course.
Such examinations often involve short-answer… See the full description on the dataset page: https://huggingface.co/datasets/IsmaelMousa/engsaf.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.multilingual-lima
Multilingual LIMA
A multilingual extension of the LIMA instruction-tuning dataset. The original English prompt–response pairs were translated into 9 additional typologically diverse languages with google/gemini-2.0-flash-001. Each language is stored as a separate Hugging Face config.
Field
Description
prompt
User instruction (translated; en is the original).
output
Assistant response (translated; en is the original).
Languages (configs): en (original), zh, it, bn… See the full description on the dataset page: https://huggingface.co/datasets/iNLP-Lab/multilingual-lima.Hinglish_Dataset_instruction_and_rawmultilingual-s1
Multilingual s1
A multilingual extension of the s1K-1.1 reasoning dataset. The original English reasoning questions and DeepSeek-R1 distilled solutions were translated into 9 additional typologically diverse languages with google/gemini-2.0-flash-001. Each language is stored as a separate Hugging Face config.
We filter the upstream simplescaling/s1K-1.1 corpus to keep only samples whose DeepSeek-R1 trajectories were marked as correctly distilled, then translate the resulting subset.… See the full description on the dataset page: https://huggingface.co/datasets/iNLP-Lab/multilingual-s1.MermaidSeqBench
Dataset Card for MermaidSeqBench
Dataset Summary
This dataset provides a human-verified benchmark for assessing large language models (LLMs) on their ability to generate Mermaid sequence diagrams from natural language prompts.
The dataset was synthetically generated using large language models (LLMs), starting from a small set of seed examples provided by a subject-matter expert. All outputs were subsequently manually verified and corrected by human annotators to ensure… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/MermaidSeqBench.Bangla-Instruct
Accepted in ACL Main 2025
TigerLLM - A Family of Bangla Large Language Models
Nishat Raihan, Marcos Zampieri
George Mason University, VA, USA
mraihan2@gmu.edu
If you find our work helpful, please consider citing our paper:
@inproceedings{raihan-zampieri-2025-tigerllm,
title = "{T}iger{LLM} - A Family of {B}angla Large Language Models",
author = "Raihan, Nishat and
Zampieri, Marcos",
editor = "Che, Wanxiang and
Nabende, Joyce and… See the full description on the dataset page: https://huggingface.co/datasets/md-nishat-008/Bangla-Instruct.Indic-post-ocr-correction
Indic Contextual Post-OCR Correction
Dataset Summary
This dataset supports contextual post-OCR correction for Indic languages. Each example is a sentence-level triple consisting of:
an OCR-generated sentence (noisy),
the preceding sentence used as context, and
the corrected sentence (ground truth).
Hugging Face dataset page:
https://huggingface.co/datasets/AbhishekBhandari/Indic-post-ocr-correction
Supported Tasks
Post-OCR text correction… See the full description on the dataset page: https://huggingface.co/datasets/AbhishekBhandari/Indic-post-ocr-correction.Institutional-Information-of-Bangladesh
Institutional-Information-of-Bangladesh Dataset
This Dataset contains all verified and authorized Institutional information in Bangladesh
Description
I have collected all data from bangladeshi government authorized web portal and also shared this link in the data source section,
this dataset is sutitable for various NLP tasks
Data Source
http://data.gov.bd/
Dataset Card Authors
Mahadi Hassan
Dataset Card Contact… See the full description on the dataset page: https://huggingface.co/datasets/Mahadih534/Institutional-Information-of-Bangladesh.idt5-v4-results-final-lora-s123-20260912T013040606815Z
final-lora-s123-20260912T013040606815Z
Run artifacts and per-item predictions.
Phase: final. These are newly generated results, not a reproduction of the legacy TCI tables.
See run_manifest.json, rules.json, generation_protocol.json and checkpoint_hashes.json. Structural scores do not establish semantic or Bloom validity.
Metrics
{
"n": 267,
"rule_version": "structural-proxy-v0.4-grounding-separated",
"parse_success_pct": 94.7565543071161,
"bleu":… See the full description on the dataset page: https://huggingface.co/datasets/Firmansyah-Ibrahim/idt5-v4-results-final-lora-s123-20260912T013040606815Z.knesset-plenums
About
This dataset is derived from raw a/v recordings and human-generated protocols of the Knesset (the Israeli house of representatives) plenums as part of the ivrit.ai project.
Consider visiting the preview space for this dataset here
Method
Data dumps from the Knesset contain A/V recordings, alongside proprietary protocols with timestamps.
We extract the audio stream, and clean up timestamp mistakes (such as backward jumps, or out-of-order timestamp artifacts).
The… See the full description on the dataset page: https://huggingface.co/datasets/ivrit-ai/knesset-plenums.Multi-IaC-Eval
Multi-IaC-Eval
We present Multi-IaC-Eval is a novel benchmark dataset for evaluating LLM-based IaC generation and mutation across AWS CloudFormation, Terraform, and Cloud Development Kit (CDK) formats. The dataset consists of triplets containing initial IaC templates, natural language modification requests, and corresponding updated templates, created through a synthetic data generation pipeline with rigorous validation.
Cloudformation: 263
Terraform: 446
CDK (Python): 64
CDK… See the full description on the dataset page: https://huggingface.co/datasets/AmazonScience/Multi-IaC-Eval.