artifact_type large_stringclasses 2
values | artifact_name large_stringlengths 5 123 | org large_stringlengths 2 42 | created_at large_stringdate 2022-03-02 00:00:00 2026-05-31 00:00:00 | last_modified large_stringdate 2020-07-16 00:00:00 2026-05-31 00:00:00 | languages listlengths 0 7.91k | license large_stringclasses 81
values | task_categories listlengths 0 47 | tags listlengths 2 7.92k | size_category large_stringclasses 11
values | downloads int64 0 262M | multilinguality listlengths 0 52 ⌀ | num_dataset_rows float64 0 194B ⌀ | disk_size float64 6 306,846B ⌀ | arxiv_ids listlengths 0 440 | readme large_stringlengths 0 13.4M |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
dataset | HuggingFaceH4/testing_alpaca_small | HuggingFaceH4 | 2023-04-12 | 2023-04-12 | [] | null | [] | [
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | n<1K | 12,792 | null | 200 | 55,262 | [] | # Dataset Card for "testing_alpaca_small"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
dataset | rameez543/polymarket_bot_data | rameez543 | 2026-04-13 | 2026-04-14 | [] | null | [] | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"region:us"
] | 1K<n<10K | 12,780 | null | 9,999 | 2,161,100,560 | [] | |
dataset | LukasMoravansky/Synth-Eye-GAN-Data | LukasMoravansky | 2026-05-12 | 2026-05-15 | [
"en"
] | mit | [
"object-detection"
] | [
"task_categories:object-detection",
"annotations_creators:machine-generated",
"multilinguality:monolingual",
"source_datasets:original",
"language:en",
"license:mit",
"size_categories:1K<n<10K",
"modality:image",
"modality:text",
"region:us",
"synthetic-data",
"stylegan2-ada",
"industrial-ai... | 1K<n<10K | 13,340 | [
"monolingual"
] | null | 94,922,805,595 | [] |
# Synth.Eye GAN — Industrial Inspection Dataset
Training dataset for the [Synth.Eye GAN](https://huggingface.co/LukasMoravansky/Synth-Eye-GAN) project —
synthetic YOLO-format images of industrial parts with and without fingerprint residue defects,
generated by three [StyleGAN2-ADA](https://github.com/LukasMoravansky/... |
dataset | NuTonic/brief-composer-sft-v1 | NuTonic | 2026-04-24 | 2026-04-25 | [
"en"
] | apache-2.0 | [] | [
"language:en",
"license:apache-2.0",
"size_categories:1K<n<10K",
"format:json",
"modality:image",
"modality:text",
"modality:geospatial",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"region:us",
"remote-sensing",
"multi-image",
"reasoning",
"vlm-sft"
... | 1K<n<10K | 13,639 | null | 8,000 | 5,430,376,390 | [] |
# BriefComposer SFT
**Multi-image** analytical **brief** rows composed from **completed** FireWatch, OceanScout, LandShift, and FloodPulse dataset folders (`metadata/` + `images/`). Each sample stitches 1–4 images and metadata-derived headlines into one **executive-style** assistant reply.
## Record counts (this bui... |
dataset | lmms-lab/RealWorldQA | lmms-lab | 2024-04-13 | 2024-04-13 | [] | cc-by-4.0 | [] | [
"license:cc-by-4.0",
"size_categories:n<1K",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | n<1K | 12,715 | null | 765 | 678,344,871 | [] | |
dataset | thainamhoang/ViMed-PET-CT | thainamhoang | 2026-04-10 | 2026-05-12 | [] | cc-by-4.0 | [
"image-to-text",
"text-generation",
"image-text-to-text"
] | [
"task_categories:image-to-text",
"task_categories:text-generation",
"task_categories:image-text-to-text",
"license:cc-by-4.0",
"size_categories:n<1K",
"modality:text",
"arxiv:2509.24739",
"region:us"
] | n<1K | 12,940 | null | 304 | 205,449,550,291 | [
"2509.24739"
] |
# ViMed-PET-CT
## 📅 Update: April 23, 2026
🐛 **Bug Fixes:** Corrected field mismatches (blank/missing fields) and date/filename inconsistencies. Restored missing metadata for patient 1701 (Dec 2023).
✨ **New Feature:** Added English translations of reports (`/reports_en`) using `Gemma-4-26B-A4B-it`.
## ℹ️ About t... |
dataset | gaianet/0xdesigner | gaianet | 2024-10-28 | 2024-10-28 | [] | null | [] | [
"size_categories:n<1K",
"format:webdataset",
"modality:text",
"library:datasets",
"library:webdataset",
"library:mlcroissant",
"region:us"
] | n<1K | 12,608 | null | 1 | 7,672,463 | [] | |
dataset | mteb/summeval | mteb | 2022-06-21 | 2025-05-03 | [
"eng"
] | mit | [
"summarization"
] | [
"task_categories:summarization",
"annotations_creators:human-annotated",
"multilinguality:monolingual",
"source_datasets:mteb/summeval",
"language:eng",
"license:mit",
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"lib... | n<1K | 12,698 | [
"monolingual"
] | 100 | 433,606 | [
"2007.12626",
"2502.13595",
"2210.07316"
] | <!-- adapted from https://github.com/huggingface/huggingface_hub/blob/v0.30.2/src/huggingface_hub/templates/datasetcard_template.md -->
<div align="center" style="padding: 40px 20px; background-color: white; border-radius: 12px; box-shadow: 0 2px 10px rgba(0, 0, 0, 0.05); max-width: 600px; margin: 0 auto;">
<h1 styl... |
dataset | HuggingFaceM4/ChartQA | HuggingFaceM4 | 2024-03-05 | 2024-03-05 | [] | gpl-3.0 | [] | [
"license:gpl-3.0",
"size_categories:10K<n<100K",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | 10K<n<100K | 12,783 | null | 32,719 | 964,098,758 | [] | # Dataset Card for "ChartQA"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
dataset | SynDataLab/irodori-clones-3m | SynDataLab | 2026-04-22 | 2026-04-23 | [
"ja"
] | apache-2.0 | [
"text-to-speech"
] | [
"task_categories:text-to-speech",
"language:ja",
"license:apache-2.0",
"size_categories:1M<n<10M",
"format:parquet",
"modality:audio",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"region:us"
] | 1M<n<10M | 12,997 | null | 2,990,000 | 2,457,878,533,889 | [] |
# Irodori TTS Voice Clones (2.99M)
Reference audios: [SynDataLab/irodori-refs-10k](https://huggingface.co/datasets/SynDataLab/irodori-refs-10k)
|
dataset | AmazonScience/massive | AmazonScience | 2022-04-27 | 2022-11-16 | [] | cc-by-4.0 | [
"text-classification"
] | [
"task_categories:text-classification",
"task_ids:intent-classification",
"task_ids:multi-class-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:af-ZA",
"multilinguality:am-ET",
"multilinguality:ar-SA",
"multilinguality:az-AZ",
"multilinguality:b... | 1M<n<10M | 12,802 | [
"af-ZA",
"am-ET",
"ar-SA",
"az-AZ",
"bn-BD",
"ca-ES",
"cy-GB",
"da-DK",
"de-DE",
"el-GR",
"en-US",
"es-ES",
"fa-IR",
"fi-FI",
"fr-FR",
"he-IL",
"hi-IN",
"hu-HU",
"hy-AM",
"id-ID",
"is-IS",
"it-IT",
"ja-JP",
"jv-ID",
"ka-GE",
"km-KH",
"kn-IN",
"ko-KR",
"lv-LV",... | 2,560,755 | 86,756 | [
"2204.08582"
] |
# MASSIVE 1.1: A 1M-Example Multilingual Natural Language Understanding Dataset with 52 Typologically-Diverse Languages
## Table of Contents
- [Dataset Card for [Needs More Information]](#dataset-card-for-needs-more-information)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-descriptio... |
dataset | ShaofantuoshuzhengzhiSha/GUIGuard-Bench | ShaofantuoshuzhengzhiSha | 2026-05-03 | 2026-05-06 | [
"en",
"zh"
] | cc-by-nc-4.0 | [
"question-answering",
"image-classification",
"visual-question-answering"
] | [
"task_categories:question-answering",
"task_categories:image-classification",
"task_categories:visual-question-answering",
"language:en",
"language:zh",
"license:cc-by-nc-4.0",
"size_categories:1K<n<10K",
"format:json",
"modality:image",
"modality:tabular",
"modality:text",
"library:datasets",... | 1K<n<10K | 13,300 | null | 2,002 | 16,438,556,777 | [] |
# GUIGuard-Bench (Public Ladder)
GUIGuard-Bench is a **cross-platform GUI agent benchmark** for studying **privacy risks and privacy-preserving execution** in multimodal GUI agents.
**This public-ladder release contains 121 GUI interaction trajectories** (68 Android + 53 PC) for benchmark evaluation, with 26,407 re... |
dataset | hf-internal-testing/compressed_files | hf-internal-testing | 2023-08-24 | 2021-08-16 | [] | null | [] | [
"size_categories:n<1K",
"format:json",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"region:us"
] | n<1K | 12,575 | null | 500 | 59,544 | [] | |
dataset | bluuebunny/arxiv_raw_dataset_by_year | bluuebunny | 2024-04-11 | 2024-04-25 | [] | null | [] | [
"size_categories:100K<n<1M",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"doi:10.57967/hf/2053",
"region:us"
] | 100K<n<1M | 12,637 | null | 148,435 | 58,972,305,048 | [] |
# Dataset Card for Dataset Name
<!-- Provide a quick summary of the dataset. -->
This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
## ... |
dataset | SwayStar123/preprocessed_commoncatalog-cc-by | SwayStar123 | 2024-10-19 | 2025-01-23 | [
"en"
] | cc-by-4.0 | [] | [
"language:en",
"license:cc-by-4.0",
"size_categories:10M<n<100M",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | 10M<n<100M | 12,901 | null | 14,581,672 | 268,514,917,891 | [] |
I also seperately provide just the prompts in prompts.json
keys are the image_id, and the values are the captions generated
Captions generated by moondream: vikhyatk/moondream2
Latents generated by SDXL VAE: madebyollin/sdxl-vae-fp16-fix
Embeddings generated by SigLIP: hf-hub:timm/ViT-SO400M-14-SigLIP-384
Origina... |
dataset | facebook/kilt_tasks | facebook | 2022-03-02 | 2024-01-04 | [
"en"
] | mit | [
"fill-mask",
"question-answering",
"text-classification",
"text-generation",
"text-retrieval",
"text2text-generation"
] | [
"task_categories:fill-mask",
"task_categories:question-answering",
"task_categories:text-classification",
"task_categories:text-generation",
"task_categories:text-retrieval",
"task_ids:abstractive-qa",
"task_ids:dialogue-modeling",
"task_ids:document-retrieval",
"task_ids:entity-linking-retrieval",
... | 1M<n<10M | 12,624 | [
"monolingual"
] | 3,231,786 | 1,050,297,550 | [
"2009.02252"
] |
# Dataset Card for KILT
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [... |
dataset | SciDrawAI/SciDraw-6K | SciDrawAI | 2026-04-18 | 2026-04-18 | [
"en",
"zh",
"ja",
"ko",
"de",
"fr",
"es",
"pt",
"it",
"ru"
] | cc-by-4.0 | [
"text-to-image"
] | [
"task_categories:text-to-image",
"language:en",
"language:zh",
"language:ja",
"language:ko",
"language:de",
"language:fr",
"language:es",
"language:pt",
"language:it",
"language:ru",
"license:cc-by-4.0",
"size_categories:1K<n<10K",
"format:parquet",
"modality:image",
"modality:text",
... | 1K<n<10K | 12,957 | null | 6,291 | 20,225,618,029 | [] |
<!-- schema note: the `image` column holds a relative path to the file under `images/`; HF will render it as a thumbnail. -->
# SciDraw-6K: A Multilingual Scientific Illustration Dataset Generated by Google Gemini
## Dataset Summary
SciDraw-6K is a curated dataset of **6,291 scientific illustrations** synthesized ... |
dataset | BrightData/Goodreads-Books | BrightData | 2024-06-19 | 2024-06-23 | [
"en"
] | other | [
"text-classification",
"summarization",
"text-generation",
"text2text-generation"
] | [
"task_categories:text-classification",
"task_categories:summarization",
"task_categories:text-generation",
"language:en",
"license:other",
"size_categories:1M<n<10M",
"format:csv",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:pola... | 1M<n<10M | 12,536 | null | 3,910,000 | 8,294,663,406 | [] | [](https://brightdata.com/)
# Dataset Card for "BrightData/Goodreads-Books"
## Dataset Summary
Explore a collection of millions of books with the Goodreads dataset, comprising over 6.3M structured records and ... |
dataset | bethgelab/dataconcept_128M | bethgelab | 2025-11-25 | 2026-02-15 | [
"en"
] | mit | [
"zero-shot-classification"
] | [
"task_categories:zero-shot-classification",
"language:en",
"license:mit",
"size_categories:100M<n<1B",
"format:parquet",
"modality:image",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"arxiv:2511.20643",
"region:us",
"C... | 100M<n<1B | 13,208 | null | 143,665,495 | 68,794,366,785 | [
"2511.20643"
] | # DataConcept-128M: Concept-Annotated Pretraining Dataset
[Paper](https://arxiv.org/abs/2511.20643) | [Code](https://github.com/bethgelab/cabs)
Correspondence: [Adhiraj Ghosh](adhirajghosh.github.io)
## 📌 Introduction
**DataConcept-128M** is a multimodal pretraining dataset comprising 128M web-crawled image-text pa... |
dataset | mlabonne/harmless_alpaca | mlabonne | 2024-05-28 | 2024-05-30 | [
"en"
] | null | [] | [
"language:en",
"size_categories:10K<n<100K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | 10K<n<100K | 12,502 | null | 31,323 | 1,217,834 | [] | |
dataset | siyanzhao/Openthoughts_math_30k_opsd | siyanzhao | 2026-02-23 | 2026-02-23 | [] | null | [] | [
"size_categories:10K<n<100K",
"format:parquet",
"format:optimized-parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"region:us"
] | 10K<n<100K | 12,561 | null | 29,434 | 279,911,583 | [] | |
dataset | lighteval/sacrebleu_manual | lighteval | 2023-04-26 | 2025-08-19 | [] | null | [] | [
"size_categories:100K<n<1M",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | 100K<n<1M | 12,686 | null | 936,212 | 154,936,957 | [] | |
dataset | shahadalkhalifa/Crypto_Whitepaper_Labeled | shahadalkhalifa | 2022-09-09 | 2022-09-09 | [] | null | [] | [
"size_categories:n<1K",
"format:csv",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | n<1K | 12,427 | null | 91 | 2,180,195 | [] | |
dataset | tiendung/cnen_novels | tiendung | 2023-09-04 | 2023-09-24 | [] | null | [] | [
"size_categories:n<1K",
"modality:text",
"region:us"
] | n<1K | 13,339 | null | 283 | 22,626,723,733 | [] | # TODOs
- Lấy:
- vi_docln.net
- cn_qidian.com
- en_novelhall
- Làm sạch data
- Loại bỏ `You can read the novel online free at novelhall.com`
- Crawl novel ranking from https://www.webnovel.com/ranking/novel/all_time/popular_rank
- Lựa chọn novels để train theo ranking từ cao tới thấp
Notes:
... |
dataset | XRXRX/X-Voice-Dataset-Train | XRXRX | 2026-04-08 | 2026-05-04 | [
"bg",
"cs",
"da",
"de",
"el",
"en",
"es",
"et",
"fr",
"fi",
"hu",
"hr",
"id",
"it",
"ja",
"ko",
"lt",
"lv",
"mt",
"nl",
"pl",
"pt",
"ro",
"ru",
"sk",
"sl",
"sv",
"th",
"vi",
"zh"
] | other | [
"text-to-speech",
"automatic-speech-recognition"
] | [
"task_categories:text-to-speech",
"task_categories:automatic-speech-recognition",
"language:bg",
"language:cs",
"language:da",
"language:de",
"language:el",
"language:en",
"language:es",
"language:et",
"language:fr",
"language:fi",
"language:hu",
"language:hr",
"language:id",
"language... | 10M<n<100M | 12,548 | null | 44,000 | 8,306,499,209,406 | [] | ---
# X-Voice Training Dataset
## Overview
The X-Voice training dataset is a **large-scale multilingual speech corpus** curated for high-performance speech models. It provides a robust foundation for cross-lingual phonetic and prosodic modeling.
Also the train set of [X-Voice Model](https://github.com/sunnyxrxrx/X-Vo... |
dataset | nyu-mll/multi_nli | nyu-mll | 2022-03-02 | 2024-01-04 | [
"en"
] | cc-by-3.0 | [
"text-classification"
] | [
"task_categories:text-classification",
"task_ids:natural-language-inference",
"task_ids:multi-input-text-classification",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"source_datasets:original",
"language:en",
"lic... | 100K<n<1M | 12,455 | [
"monolingual"
] | 412,349 | 224,015,292 | [] |
# Dataset Card for Multi-Genre Natural Language Inference (MultiNLI)
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure... |
dataset | dgslibisey/MuSiQue | dgslibisey | 2023-06-14 | 2023-06-16 | [] | null | [] | [
"size_categories:10K<n<100K",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | 10K<n<100K | 12,437 | null | 22,355 | 271,488,940 | [] | |
dataset | Mutonix/Vript | Mutonix | 2024-04-10 | 2024-06-11 | [
"en"
] | null | [
"video-classification",
"visual-question-answering",
"text-to-video",
"text-to-image",
"image-to-video"
] | [
"task_categories:video-classification",
"task_categories:visual-question-answering",
"task_categories:text-to-video",
"task_categories:text-to-image",
"task_categories:image-to-video",
"language:en",
"size_categories:100K<n<1M",
"format:json",
"modality:text",
"modality:video",
"library:datasets... | 100K<n<1M | 12,597 | null | 408,816 | 1,620,344,227,725 | [
"2406.06040"
] | # 🎬 Vript: Refine Video Captioning into Video Scripting [[Github Repo](https://github.com/mutonix/Vript)]
---
We construct a **fine-grained** video-text dataset with 12K annotated high-resolution videos **(~400k clips)**. The annotation of this dataset is inspired by the video script. If we want to make a video, we ha... |
dataset | FastVideo/Wan2.2-Syn-121x704x1280_32k | FastVideo | 2025-08-04 | 2025-10-29 | [] | apache-2.0 | [
"text-to-video"
] | [
"task_categories:text-to-video",
"license:apache-2.0",
"size_categories:10K<n<100K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2505.13389",
"arxiv:2502.04507",
"region:us",
"fastvideo",
"synt... | 10K<n<100K | 12,488 | null | 33,336 | 865,984,486,305 | [
"2505.13389",
"2502.04507"
] |
# FastVideo Synthetic Wan2.2 720P dataset
<p align="center">
<img src="https://raw.githubusercontent.com/hao-ai-lab/FastVideo/main/assets/logo.png" width="200"/>
</p>
<div>
<div align="center">
<a href="https://github.com/hao-ai-lab/FastVideo" target="_blank">FastVideo Team</a> 
</div>
<div align="ce... |
dataset | instruction-pretrain/general-instruction-augmented-corpora | instruction-pretrain | 2024-06-24 | 2026-03-02 | [
"en"
] | odc-by | [
"text-classification",
"table-question-answering",
"question-answering",
"zero-shot-classification"
] | [
"task_categories:text-classification",
"task_categories:table-question-answering",
"task_categories:question-answering",
"task_categories:zero-shot-classification",
"language:en",
"license:odc-by",
"modality:text",
"arxiv:2406.14491",
"arxiv:2601.16206",
"arxiv:2309.09530",
"region:us"
] | null | 12,542 | null | null | 135,796,969,058 | [
"2406.14491",
"2601.16206",
"2309.09530"
] |
# Instruction Pre-Training: Language Models are Supervised Multitask Learners (EMNLP 2024)
This repo contains the **general instruction-augmented corpora** (containing 200M instruction-response pairs covering 40+ task categories) used in our paper [Instruction Pre-Training: Language Models are Supervised Multitask Lea... |
dataset | BangumiBase/apocalypsehotel | BangumiBase | 2025-08-07 | 2025-08-07 | [] | mit | [] | [
"license:mit",
"size_categories:1K<n<10K",
"modality:image",
"modality:text",
"region:us",
"art"
] | 1K<n<10K | 12,399 | null | null | 10,730,638,968 | [] |
# Bangumi Image Base of Apocalypse Hotel
This is the image base of bangumi Apocalypse Hotel, we detected 45 characters, 4277 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100% cleaned, they may be noisy actual.** If you intend to manually train mo... |
dataset | trl-internal-testing/harmony | trl-internal-testing | 2025-08-05 | 2025-12-15 | [] | null | [] | [
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | n<1K | 12,428 | null | 57 | 40,194 | [] | |
dataset | danish-foundation-models/danish-dynaword | danish-foundation-models | 2024-12-15 | 2026-04-30 | [
"da"
] | cc0-1.0 | [
"text-generation"
] | [
"task_categories:text-generation",
"task_ids:language-modeling",
"annotations_creators:no-annotation",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"source_datasets:original",
"language:da",
"license:cc0-1.0",
"size_categories:10M<n<100M",
"format:parquet",
"modality:image",
... | 10M<n<100M | 12,304 | [
"monolingual"
] | 11,324,052 | 10,536,918,000 | [
"2508.02271"
] |
<!--
readme structure is inspired by:
https://github.com/huggingface/datasets/blob/main/templates/README_guide.md
-->
# 🧨 Danish Dynaword
<!-- START README TABLE -->
| | ... |
dataset | walledai/AdvBench | walledai | 2024-07-02 | 2024-07-04 | [
"en"
] | mit | [
"text2text-generation"
] | [
"language:en",
"license:mit",
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"arxiv:2307.15043",
"region:us"
] | n<1K | 12,392 | null | null | 39,035 | [
"2307.15043"
] |
# Dataset Card for AdvBench
Paper: [Universal and Transferable Adversarial Attacks on Aligned Language Models](https://arxiv.org/abs/2307.15043)
Data: [AdvBench Dataset](https://github.com/llm-attacks/llm-attacks/blob/main/data/advbench/harmful_behaviors.csv)
## About
AdvBench is a set of 500 harmful behaviors form... |
dataset | lockon/xlam-function-calling-60k | lockon | 2025-08-11 | 2025-01-24 | [
"en"
] | cc-by-4.0 | [
"question-answering",
"text-generation",
"reinforcement-learning"
] | [
"task_categories:question-answering",
"task_categories:text-generation",
"task_categories:reinforcement-learning",
"language:en",
"license:cc-by-4.0",
"size_categories:10K<n<100K",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
... | 10K<n<100K | 12,311 | null | 60,000 | 97,680,202 | [
"2406.18518"
] |
# APIGen Function-Calling Datasets
[Paper](https://arxiv.org/abs/2406.18518) | [Website](https://apigen-pipeline.github.io/) | [Models](https://huggingface.co/collections/Salesforce/xlam-models-65f00e2a0a63bbcd1c2dade4)
This repo contains 60,000 data collected by [APIGen](https://apigen-pipeline.github.io/), an aut... |
dataset | HuggingFaceTB/smoltalk2 | HuggingFaceTB | 2025-07-10 | 2025-10-31 | [] | null | [] | [
"size_categories:1M<n<10M",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2410.15553",
"arxiv:2412.15115",
"region:us"
] | 1M<n<10M | 12,441 | null | 8,610,022 | 87,741,812,980 | [
"2410.15553",
"2412.15115"
] |
# SmolTalk2
## Dataset description
This dataset contains three subsets (Mid, SFT, Preference) that correspond to the three phases of Post-Training for [SmolLM3-3B](https://huggingface.co/HuggingFac... |
dataset | Ravenh97/generated_video | Ravenh97 | 2026-05-09 | 2026-05-27 | [] | null | [] | [
"size_categories:10K<n<100K",
"modality:text",
"modality:video",
"library:datasets",
"library:mlcroissant",
"region:us"
] | 10K<n<100K | 13,086 | null | 21,670 | 5,729,295,006 | [] | |
dataset | kairusama/ris-one | kairusama | 2026-05-05 | 2026-05-11 | [] | cc0-1.0 | [] | [
"license:cc0-1.0",
"size_categories:1M<n<10M",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"region:us",
"finance",
"banking",
"fdic",
"ris",
"research-information-system",
"parquet"
] | 1M<n<10M | 12,446 | null | 4,169,912 | 3,279,273,651 | [] |
# FDIC Research Information System (RIS)
Curated Parquet snapshots of the **FDIC Research Information System (RIS)** —
the public bulk dataset distributed by the FDIC through its FOIA page.
## What is RIS?
The FDIC Research Information System is a relational database of bank structure
and financial data covering al... |
dataset | AdaMLLab/KorMix | AdaMLLab | 2026-05-01 | 2026-05-11 | [
"ko"
] | other | [
"text-generation"
] | [
"task_categories:text-generation",
"language:ko",
"license:other",
"size_categories:100M<n<1B",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"arxiv:2512.18834",
"region:us"
] | 100M<n<1B | 12,416 | null | 210,152,231 | 350,101,926,139 | [
"2512.18834"
] |
<p align="center">
<a href="https://huggingface.co/collections/AdaMLLab/mixminmatch">
<img src="https://img.shields.io/badge/🤗_Collection-MixMinMatch-blue" alt="MixMinMatch Collection">
</a>
</p>
KorMix ([https://arxiv.org/abs/2512.18834](https://arxiv.org/abs/2512.18834)) is a Korean pretraining corpus buil... |
dataset | allenai/olmo-mix-1124 | allenai | 2024-11-24 | 2025-08-19 | [
"en"
] | odc-by | [
"text-generation"
] | [
"task_categories:text-generation",
"language:en",
"license:odc-by",
"size_categories:100M<n<1B",
"modality:text",
"region:us"
] | 100M<n<1B | 13,029 | null | 3,257,607 | 7,481,737,655,343 | [] |
# OLMo 2 (November 2024) Pretraining set
Collection of data used to train OLMo-2-1124 models. The majority of this dataset comes from DCLM-Baseline with no additional filtering, but we provide the explicit breakdowns below.
| Name | Tokens | Bytes (uncompressed) | Documents | License |
|----------------... |
dataset | bespokelabs/Bespoke-Stratos-17k | bespokelabs | 2025-01-21 | 2025-01-31 | [
"en"
] | apache-2.0 | [] | [
"language:en",
"license:apache-2.0",
"size_categories:10K<n<100K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us",
"curator",
"synthetic"
] | 10K<n<100K | 12,299 | null | 16,710 | 126,171,198 | [] |
<p align="center">
<a href="https://bespokelabs.ai"><img src="Bespoke-Labs-Logo-on-Mint.png" width="550"></a>
</p>
## Bespoke-Stratos-17k
[We](https://bespokelabs.ai) replicated and improved the [Berkeley Sky-T1](https://novasky-ai.github.io/posts/sky-t1/) data pipeline using SFT distillation data
from [DeepSee... |
dataset | Apokryf/SJP | Apokryf | 2026-03-09 | 2026-03-10 | [
"pl"
] | gpl-2.0 | [
"text-classification",
"token-classification",
"translation",
"summarization",
"text-generation",
"sentence-similarity"
] | [
"task_categories:text-classification",
"task_categories:token-classification",
"task_categories:translation",
"task_categories:summarization",
"task_categories:text-generation",
"task_categories:sentence-similarity",
"language:pl",
"license:gpl-2.0",
"modality:text",
"region:us",
"art",
"legal... | null | 12,790 | null | null | 300,462,944 | [] |
# [SJP](https://sjp.pl/)
# Słownik Języka Polskiego
> transferowany z oficjalnych zasobników zestaw słownikowy do pracy z językiem polskim.
> https://sjp.pl/
|
dataset | togethercomputer/CoderForge-Preview | togethercomputer | 2026-02-20 | 2026-02-26 | [] | null | [] | [
"size_categories:100K<n<1M",
"format:parquet",
"format:optimized-parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"doi:10.57967/hf/8626",
"region:us"
] | 100K<n<1M | 12,343 | null | 826,556 | 72,774,674,929 | [] |
# CoderForge-Preview: SOTA Open Dataset for Training Efficient Agents
**CoderForge-Preview** is **the** **largest open test-verified coding agent dataset.**
Fine-tuning Qwen-3 32B on it, we boost **SWE-Bench Verified performance** **23.0% → 59.4% pass@1** and rank **#1 among open-data** and **#2 among open-weight ... |
dataset | qruisjtu/EmbodiedRestore | qruisjtu | 2026-05-05 | 2026-05-05 | [
"en"
] | odc-by | [
"image-to-image",
"robotics",
"other"
] | [
"task_categories:image-to-image",
"task_categories:robotics",
"task_categories:other",
"language:en",
"license:odc-by",
"size_categories:10K<n<100K",
"format:csv",
"modality:image",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroi... | 10K<n<100K | 13,051 | null | 37,525 | 1,744,357,410 | [] |
# EmbodiedRestore
Paired robotic first-frame observations (low-quality / ground-truth) under 25 distortions from the TID2013 / KADID-10k taxonomy, evaluated by three policies (π0.5, π0, OpenVLA). Built for benchmarking image restoration / IQA on robot-observation distributions, with downstream policy success rates(SR... |
dataset | PGLearn/PGLearn-Small-89_pegase | PGLearn | 2025-04-17 | 2025-04-18 | [] | cc-by-sa-4.0 | [
"tabular-regression"
] | [
"task_categories:tabular-regression",
"license:cc-by-sa-4.0",
"size_categories:100K<n<1M",
"format:parquet",
"modality:tabular",
"modality:text",
"modality:timeseries",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us",
"energy",
"optimization",
"op... | 100K<n<1M | 12,229 | null | 880,990 | 50,015,178,389 | [] | |
dataset | sleeping-ai/genius | sleeping-ai | 2025-01-22 | 2025-02-12 | [] | mit | [
"feature-extraction"
] | [
"task_categories:feature-extraction",
"license:mit",
"size_categories:1M<n<10M",
"format:csv",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us",
"music"
] | 1M<n<10M | 12,176 | null | 8,885,602 | 15,225,771,945 | [] |
<div style="display: flex; flex-direction: column; align-items: center; justify-content: center; height: 100vh;">
<h1 style="text-align: center;">GENIUS</h1>
<img src="genius.png" alt="Genius" width="200"/>
</div>
Genius, originally known as Rap Genius, was created as a platform for annotating rap music lyrics... |
dataset | toxigen/toxigen-data | toxigen | 2022-05-01 | 2024-06-17 | [] | null | [
"text-classification"
] | [
"task_categories:text-classification",
"task_ids:hate-speech-detection",
"annotations_creators:expert-generated",
"language_creators:machine-generated",
"multilinguality:monolingual",
"source_datasets:original",
"size_categories:100K<n<1M",
"format:parquet",
"modality:tabular",
"modality:text",
... | 100K<n<1M | 12,275 | [
"monolingual"
] | 319,301 | 219,019,973 | [
"2203.09509"
] |
# Dataset Card for ToxiGen
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Fields](#data-instances)
- [Additional Information](#additional-information)
- [Citation Information](... |
dataset | sy1998/MLVU_Test | sy1998 | 2025-03-12 | 2025-03-15 | [] | null | [] | [
"size_categories:n<1K",
"format:parquet",
"modality:text",
"modality:video",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | n<1K | 12,141 | null | 502 | 75,359,450,310 | [] | |
dataset | ai4bharat/IndicParaphrase | ai4bharat | 2022-03-09 | 2022-10-13 | [
"as",
"bn",
"gu",
"hi",
"kn",
"ml",
"mr",
"or",
"pa",
"ta",
"te"
] | cc-by-nc-4.0 | [
"conditional-text-generation"
] | [
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:multilingual",
"source_datasets:original",
"language:as",
"language:bn",
"language:gu",
"language:hi",
"language:kn",
"language:ml",
"language:mr",
"language:or",
"language:pa",
"language:ta",
"language:te"... | 1M<n<10M | 12,165 | [
"multilingual"
] | 5,564,833 | 798,378,451 | [
"2203.05437"
] |
# Dataset Card for "IndicParaphrase"
## Table of Contents
- [Dataset Card Creation Guide](#dataset-card-creation-guide)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-le... |
dataset | BangumiBase/guildnouketsukejoudesugazangyouwaiyananodebosswosolotoubatsushiyoutoomoimasu | BangumiBase | 2025-08-07 | 2025-08-07 | [] | mit | [] | [
"license:mit",
"size_categories:1K<n<10K",
"modality:image",
"modality:text",
"region:us",
"art"
] | 1K<n<10K | 12,186 | null | null | 11,645,401,434 | [] |
# Bangumi Image Base of Guild No Uketsukejou Desu Ga, Zangyou Wa Iya Nanode Boss Wo Solo Toubatsu Shiyou To Omoimasu
This is the image base of bangumi Guild no Uketsukejou desu ga, Zangyou wa Iya nanode Boss wo Solo Toubatsu Shiyou to Omoimasu, we detected 64 characters, 4480 images in total. The full dataset is [her... |
dataset | ceselder/gemma3-4b-system-prompt-loras | ceselder | 2026-03-16 | 2026-03-16 | [] | null | [] | [
"size_categories:10K<n<100K",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"region:us"
] | 10K<n<100K | 12,208 | null | 24,055 | 39,522,086,181 | [] | |
dataset | thu-coai/chid | thu-coai | 2023-05-08 | 2023-05-08 | [
"zh"
] | apache-2.0 | [] | [
"language:zh",
"license:apache-2.0",
"size_categories:100K<n<1M",
"format:text",
"modality:text",
"library:datasets",
"library:mlcroissant",
"arxiv:1906.01265",
"region:us"
] | 100K<n<1M | 12,132 | null | 711,965 | 723,501,941 | [
"1906.01265"
] |
The ChID dataset. [GitHub repo](https://github.com/chujiezheng/ChID-Dataset). [Original paper](https://arxiv.org/abs/1906.01265).
```bib
@inproceedings{zheng-etal-2019-chid,
title = "{C}h{ID}: A Large-scale {C}hinese {ID}iom Dataset for Cloze Test",
author = "Zheng, Chujie and
Huang, Minlie and
... |
dataset | GAIA-Grand-defi-robotique-agricole/techno_dataset | GAIA-Grand-defi-robotique-agricole | 2025-02-25 | 2025-02-25 | [] | null | [] | [
"size_categories:n<1K",
"format:json",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"region:us"
] | n<1K | 12,027 | null | 6 | 315,797 | [] | |
dataset | MultiTalk/MultiTalkFT | MultiTalk | 2026-05-05 | 2026-05-08 | [
"zh",
"en"
] | cc-by-nc-4.0 | [
"audio-to-audio"
] | [
"task_categories:audio-to-audio",
"language:zh",
"language:en",
"license:cc-by-nc-4.0",
"size_categories:n<1K",
"format:parquet",
"modality:audio",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"region:us",
"speech",
"dialogue",
"multi-... | n<1K | 13,410 | null | 100 | 488,359,886,193 | [] |
# MultiTalkFT
Fine-tuning corpus for full-duplex multi-speaker dialogue.
## Schemas
`data_{zh,en}{,_multichannel}.jsonl` (one record per line):
| field | type | description |
|------------|----------|------------------------------------------------------|
| `path` ... |
dataset | anusfoil/ycuppe-midi | anusfoil | 2026-03-26 | 2026-03-27 | [] | cc-by-4.0 | [
"audio-classification"
] | [
"task_categories:audio-classification",
"license:cc-by-4.0",
"size_categories:1K<n<10K",
"format:csv",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"region:us",
"piano",
"midi",
"performance-assessment",
"music"
] | 1K<n<10K | 12,133 | null | 5,022 | 5,208,291 | [] |
# YCU-PPE-III: Piano Performance MIDI Dataset
MIDI transcriptions of the YCU-PPE-III piano performance dataset (Wang et al.), used for **unreferenced Performance MOS (PMOS) prediction** in [EVPMR](https://github.com/anusfoil/eval-piano-midi-repr).
## Overview
- **2,627 MIDI files** transcribed from WAV recordings v... |
dataset | Amshaker/Qwen-RL | Amshaker | 2026-02-22 | 2026-04-01 | [] | null | [] | [
"size_categories:n<1K",
"modality:tabular",
"modality:text",
"region:us"
] | n<1K | 12,072 | null | 2 | 238,589,271,007 | [] | |
dataset | laion/laions_got_talent | laion | 2024-11-04 | 2025-01-05 | [] | null | [] | [
"size_categories:100K<n<1M",
"format:webdataset",
"modality:audio",
"modality:text",
"library:datasets",
"library:webdataset",
"library:mlcroissant",
"region:us"
] | 100K<n<1M | 12,050 | null | 5,600 | 418,933,892,596 | [] |
# LAION's Got Talent: Generated Voice Acting Dataset
## Overview
"LAION's Got Talent" is a generated dataset comprising voice acting samples that exhibit a wide range of emotions, vocal bursts, topics, and content. This dataset is a component of the BUD-E project, spearheaded by LAION with support from Intel.
## ... |
dataset | garak-llm/drh-System-Prompt-processed | garak-llm | 2026-04-23 | 2026-04-23 | [] | apache-2.0 | [] | [
"license:apache-2.0",
"size_categories:n<1K",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"region:us"
] | n<1K | 12,066 | null | 944 | 1,467,412 | [] | |
dataset | m-a-p/SciMMIR | m-a-p | 2024-01-17 | 2024-01-25 | [] | null | [] | [
"size_categories:100K<n<1M",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2401.13478",
"region:us"
] | 100K<n<1M | 12,065 | null | 530,975 | 63,730,294,378 | [
"2401.13478"
] | # Dataset Card for "SciMMIR_dataset"
## SciMMIR
This is the repo for the paper [SciMMIR： Benchmarking Scientific Multi-modal Information Retrieval](https://arxiv.org/abs/2401.13478).
In this paper, we propose a novel SciMMIR benchmark and a corresponding dataset designed to addre... |
dataset | AliHome3D/SA-BENCH | AliHome3D | 2026-05-12 | 2026-05-12 | [
"en"
] | apache-2.0 | [
"image-classification"
] | [
"task_categories:image-classification",
"language:en",
"license:apache-2.0",
"size_categories:10K<n<100K",
"format:csv",
"modality:image",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"region:us",
"image",
"image-qual... | 10K<n<100K | 12,753 | null | 35,521 | 15,663,653,963 | [] |
# SA-BENCH
SA-BENCH is the benchmark dataset released with **“Beyond Pixels: Benchmarking and Reward-Based Assessing Framework for Visual Spatial Aesthetics.”**
It evaluates the spatial aesthetics of interior images along four dimensions:
- **distortion**
- **harmony**
- **layout**
- **lighting**
The dataset conta... |
dataset | garak-llm/tm-system_prompt | garak-llm | 2026-01-12 | 2026-01-12 | [] | cc-by-4.0 | [] | [
"license:cc-by-4.0",
"size_categories:n<1K",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"region:us"
] | n<1K | 12,035 | null | 69 | 17,897 | [] | |
dataset | taeminlee/Ko-StrategyQA | taeminlee | 2024-01-12 | 2025-05-07 | [
"ko"
] | null | [
"text-retrieval"
] | [
"task_categories:text-retrieval",
"task_ids:document-retrieval",
"multilinguality:monolingual",
"source_datasets:Ko-StrategyQA",
"language:ko",
"size_categories:10K<n<100K",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region... | 10K<n<100K | 12,016 | [
"monolingual"
] | 41,774 | 14,966,767 | [] |
# Ko-StrategyQA
This dataset represents a conversion of the [Ko-StrategyQA dataset](https://huggingface.co/datasets/NomaDamas/Ko-StrategyQA) into the [BeIR](https://github.com/beir-cellar/beir) format, making it compatible for use with [mteb](https://github.com/embeddings-benchmark/mteb).
The original dataset was de... |
dataset | m-a-p/Matrix | m-a-p | 2024-05-08 | 2025-02-25 | [
"en",
"zh"
] | apache-2.0 | [
"text-generation"
] | [
"task_categories:text-generation",
"language:en",
"language:zh",
"license:apache-2.0",
"size_categories:1B<n<10B",
"format:json",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"region:us",
"language model"
] | 1B<n<10B | 12,041 | null | 2,499,047 | 19,924,136,815,239 | [] |
# Matrix
An open-source pretraining dataset containing 4690 billion tokens, this bilingual dataset with both English and Chinese texts is used for training neo models.
## Dataset Composition
The dataset consists of several components, each originating from different sources and serving various purposes in language ... |
dataset | open-thoughts/AgentTrove | open-thoughts | 2026-04-27 | 2026-05-07 | [
"en"
] | apache-2.0 | [
"text-generation"
] | [
"task_categories:text-generation",
"language:en",
"license:apache-2.0",
"size_categories:1M<n<10M",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"region:us",
"agent",
"code",
"agentic-traces",
"reinforcement-learning",
... | 1M<n<10M | 12,024 | null | 1,696,847 | 19,552,366,847 | [] |
# AgentTrove
**AgentTrove** is the largest open-source collection of agentic interaction traces to date, released by the [OpenThoughts-Agent](https://www.open-thoughts.ai/blog/agent) team. It contains **1,696,847 rows** drawn from 219 source datasets spanning code repair, shell scripting, mathematical problem-solving... |
dataset | bigcode/the-stack-metadata | bigcode | 2022-12-19 | 2023-03-16 | [
"code"
] | other | [
"text-generation"
] | [
"task_categories:text-generation",
"language_creators:crowdsourced",
"language_creators:expert-generated",
"multilinguality:multilingual",
"language:code",
"license:other",
"size_categories:10B<n<100B",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
... | 10B<n<100B | 12,124 | [
"multilingual"
] | 10,803,361,329 | 603,123,336,019 | [
"2211.15533"
] |
# Dataset Card for The Stack Metadata
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Changelog](#changelog)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Dataset Structure](#datase... |
dataset | israel/ProverbEval | israel | 2024-07-18 | 2025-05-27 | [] | null | [] | [
"size_categories:10K<n<100K",
"format:csv",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"arxiv:2411.05049",
"region:us"
] | 10K<n<100K | 12,047 | null | 50,552 | 15,204,772 | [
"2411.05049"
] |
# ProverbEval: Benchmark for Evaluating LLMs on Low-Resource Proverbs
This dataset accompanies the paper:
**"ProverbEval: Exploring LLM Evaluation Challenges for Low-resource Language Understanding"**
[ArXiv:2411.05049v3](https://arxiv.org/abs/2411.05049)
## Dataset Summary
**ProverbEval** is a culturally gro... |
dataset | bigcode/the-stack-dedup | bigcode | 2022-10-06 | 2023-08-17 | [
"code"
] | other | [
"text-generation"
] | [
"task_categories:text-generation",
"language_creators:crowdsourced",
"language_creators:expert-generated",
"multilinguality:multilingual",
"language:code",
"license:other",
"size_categories:100M<n<1B",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
... | 100M<n<1B | 12,041 | [
"multilingual"
] | null | 996,367,436,829 | [
"2211.15533",
"2107.03374",
"2207.14157"
] |
# Dataset Card for The Stack
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Changelog](#changelog)
- [Dataset Summary](#dataset-summary)
- [S... |
dataset | anonresearch-ai/tinyInWARD | anonresearch-ai | 2026-04-28 | 2026-04-30 | [] | cc-by-nc-sa-4.0 | [] | [
"license:cc-by-nc-sa-4.0",
"size_categories:1M<n<10M",
"format:parquet",
"modality:image",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"region:us"
] | 1M<n<10M | 12,625 | null | 1,984,932 | 2,306,474,739 | [] | |
dataset | paint-by-inpaint/PIPE | paint-by-inpaint | 2024-06-05 | 2025-06-27 | [] | cc-by-4.0 | [
"image-to-image"
] | [
"task_categories:image-to-image",
"license:cc-by-4.0",
"size_categories:1M<n<10M",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2404.18212",
"region:us"
] | 1M<n<10M | 11,949 | null | 1,777,212 | 80,461,143,971 | [
"2404.18212"
] |
# Dataset Card for PIPE Dataset
## Dataset Summary
The PIPE (Paint by InPaint Edit) dataset is designed to enhance the efficacy of mask-free, instruction-following image editing models by providing a large-scale collection of image pairs and diverse object addition instructions. Comprising approximately 1 million im... |
dataset | TheGreatRambler/mm2_level | TheGreatRambler | 2022-09-18 | 2022-11-11 | [
"multilingual"
] | cc-by-nc-sa-4.0 | [
"other",
"object-detection",
"text-retrieval",
"token-classification",
"text-generation"
] | [
"task_categories:other",
"task_categories:object-detection",
"task_categories:text-retrieval",
"task_categories:token-classification",
"task_categories:text-generation",
"multilinguality:multilingual",
"source_datasets:original",
"language:multilingual",
"license:cc-by-nc-sa-4.0",
"size_categories... | 10M<n<100M | 11,789 | [
"multilingual"
] | 26,609,725 | 85,472,461,688 | [] |
# Mario Maker 2 levels
Part of the [Mario Maker 2 Dataset Collection](https://tgrcode.com/posts/mario_maker_2_datasets)
## Dataset Description
The Mario Maker 2 levels dataset consists of 26.6 million levels from Nintendo's online service totaling around 100GB of data. The dataset was created using the self-hosted [M... |
dataset | loopnav/loopnav | loopnav | 2026-05-05 | 2026-05-06 | [] | mit | [] | [
"license:mit",
"size_categories:10K<n<100K",
"format:csv",
"modality:text",
"modality:video",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"region:us"
] | 10K<n<100K | 12,138 | null | 19,200 | 652,337,739,603 | [] | |
dataset | paridhidchoudhary/persuasort-dataset | paridhidchoudhary | 2026-05-05 | 2026-05-06 | [] | null | [] | [
"modality:text",
"region:us"
] | null | 12,212 | null | null | 882,269,637 | [] | |
dataset | dchasap/spec_cpu_branch_traces | dchasap | 2024-05-16 | 2024-07-25 | [] | null | [] | [
"size_categories:10B<n<100B",
"format:json",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | 10B<n<100B | 11,806 | null | 238,289,805 | 845,696,489,881 | [] | |
dataset | lewtun/ml-intern-sessions | lewtun | 2026-05-01 | 2026-05-13 | [
"en"
] | other | [
"text-generation"
] | [
"task_categories:text-generation",
"language:en",
"license:other",
"size_categories:n<1K",
"format:json",
"format:agent-traces",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"region:us",
"agent-traces",
"coding-agent",
... | n<1K | 11,767 | null | 223 | 11,371,908 | [] |
# ML Intern session traces
This dataset contains ML Intern coding agent session traces uploaded from local
ML Intern runs. The traces are stored as JSON Lines files under `sessions/`,
with one file per session.
## Links
- ML Intern demo: https://smolagents-ml-intern.hf.space
- ML Intern CLI: https://github.com/hugg... |
dataset | jiyu9437/gaia_subset | jiyu9437 | 2025-07-16 | 2025-07-16 | [] | null | [] | [
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | n<1K | 11,897 | null | 32 | 16,880 | [] | |
dataset | Aynursusuz/tts-pretrain-2m | Aynursusuz | 2026-03-30 | 2026-03-31 | [] | null | [] | [
"size_categories:1M<n<10M",
"format:parquet",
"modality:audio",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"region:us"
] | 1M<n<10M | 12,022 | null | 2,000,000 | 2,937,585,770,250 | [] |
# TTS Pretrain 2M
2M synthetic TTS audio samples across 2000 speakers.
- **Speakers**: 2000 (speaker_00001001 through speaker_00003000)
- **Samples per speaker**: 1000 (10 clones x 100 texts)
- **Total samples**: 2,000,000
- **Sample rate**: 44.1 kHz
- **Format**: WAV embedded in Parquet
|
dataset | FDlalala/tranS | FDlalala | 2025-09-30 | 2026-05-28 | [
"en"
] | cc-by-nc-4.0 | [
"audio-classification",
"automatic-speech-recognition"
] | [
"task_categories:audio-classification",
"task_categories:automatic-speech-recognition",
"language:en",
"license:cc-by-nc-4.0",
"size_categories:100K<n<1M",
"format:parquet",
"modality:audio",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"librar... | 100K<n<1M | 12,151 | null | 243,295 | 7,974,031,752 | [
"2505.19978"
] | # DeepDialogue-xtts
**DeepDialogue-xtts** is a large-scale multimodal dataset containing 40,150 high-quality multi-turn dialogues spanning 41 domains and incorporating 20 distinct emotions with coherent emotional progressions.
This repository contains the XTTS-v2 variant of the dataset, where speech is generated u... |
dataset | fishingguy/UltraData-Math | fishingguy | 2026-04-02 | 2026-04-02 | [
"en",
"zh"
] | apache-2.0 | [
"text-generation"
] | [
"task_categories:text-generation",
"language:en",
"language:zh",
"license:apache-2.0",
"size_categories:100M<n<1B",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"region:us",
"llm",
"pretraining",
"math",
"data-synthesis... | 100M<n<1B | 11,755 | null | 181,186,453 | 552,413,407,986 | [] |
# UltraData-Math
<div align="center">
<img src="assets/ultradata-math-logo.png" width="600"/>
</div>
<p align="center">
<a href="https://huggingface.co/datasets/openbmb/UltraData-Math">🤗 Dataset</a> | <a href="https://github.com/UltraData-OpenBMB/UltraData-Math">💻 Source Code</a> | <a href="https://huggingface.c... |
dataset | xlangai/spider | xlangai | 2022-03-02 | 2024-03-27 | [
"en"
] | cc-by-sa-4.0 | [
"text2text-generation"
] | [
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language_creators:machine-generated",
"multilinguality:monolingual",
"source_datasets:original",
"language:en",
"license:cc-by-sa-4.0",
"size_categories:1K<n<10K",
"format:parquet",
"modality:text",
"library:datasets... | 1K<n<10K | 11,958 | [
"monolingual"
] | 8,034 | 963,930 | [
"1809.08887"
] |
# Dataset Card for Spider
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
... |
dataset | Lichess/standard-chess-games | Lichess | 2024-09-24 | 2025-10-16 | [] | cc0-1.0 | [] | [
"license:cc0-1.0",
"size_categories:1B<n<10B",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us",
"chess",
"games",
"game",
"lichess",
"tabular"
] | 1B<n<10B | 12,269 | null | 7,136,017,970 | 4,938,473,326,231 | [] |
> [!CAUTION]
> This dataset is still a work in progress and some breaking changes might occur.
>
# Lichess Rated Standard Chess Games Dataset
## Dataset Description
**6,771,826,271** standard rated games, played on [lichess.org](https://lichess.org), updated monthly from the [database dumps](https://database.liches... |
dataset | ysy31415926/EffectData | ysy31415926 | 2026-03-03 | 2026-05-02 | [
"en",
"zh"
] | apache-2.0 | [
"image-to-video",
"text-to-video"
] | [
"task_categories:image-to-video",
"task_categories:text-to-video",
"language:en",
"language:zh",
"license:apache-2.0",
"size_categories:1K<n<10K",
"modality:text",
"library:datasets",
"library:mlcroissant",
"arxiv:2603.06014",
"region:us"
] | 1K<n<10K | 11,867 | null | 3,061 | 822,279,815,876 | [
"2603.06014"
] |
# EffectData
This repository contains the dataset released with the paper **"EffectMaker: Unifying Reasoning and Generation for Customized Visual Effect Creation"**.
> [Shiyuan Yang](https://scholar.google.com/citations?user=gIVxcEoAAAAJ&hl)1,2,†,*, [Ruihuang Li](https://scholar.google.com/citations?user=8CfyOtQAAAAJ... |
dataset | CleverThis/freebase | CleverThis | 2025-12-08 | 2025-12-08 | [
"en"
] | cc-by-2.5 | [
"text-generation",
"feature-extraction"
] | [
"task_categories:text-generation",
"task_categories:feature-extraction",
"language:en",
"license:cc-by-2.5",
"size_categories:1B<n<10B",
"format:parquet",
"format:optimized-parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"region:us",
... | 1B<n<10B | 11,786 | null | 3,130,753,066 | 32,476,443,230 | [] |
# Freebase
## Dataset Description
Large-scale knowledge base (archived by Google)
**Original Source:** http://commondatastorage.googleapis.com/freebase-public/rdf/freebase-rdf-latest.gz
### Dataset Summary
This dataset contains RDF triples from Freebase converted to HuggingFace
dataset format for easy use in mach... |
dataset | igfbench-neurips2026/IGF-Bench | igfbench-neurips2026 | 2026-05-02 | 2026-05-03 | [
"en"
] | cc-by-nc-sa-4.0 | [
"depth-estimation",
"image-to-image",
"text-to-image"
] | [
"task_categories:depth-estimation",
"task_categories:image-to-image",
"task_categories:text-to-image",
"language:en",
"license:cc-by-nc-sa-4.0",
"size_categories:n<1K",
"format:json",
"modality:image",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars... | n<1K | 12,091 | null | 43 | 158,797,401,768 | [] |
# IGF-Bench: Indoor Geometric Fidelity Benchmark
> **Anonymous mirror for NeurIPS 2026 Evaluations and Datasets Track double-blind review.**
> The de-anonymised author/maintainer information will replace this header at camera-ready.
**IGF-Bench** is the first benchmark for evaluating **structural-level geometric fid... |
dataset | openai/MMMLU | openai | 2024-09-13 | 2024-10-16 | [
"ar",
"bn",
"de",
"es",
"fr",
"hi",
"id",
"it",
"ja",
"ko",
"pt",
"sw",
"yo",
"zh"
] | mit | [
"question-answering"
] | [
"task_categories:question-answering",
"language:ar",
"language:bn",
"language:de",
"language:es",
"language:fr",
"language:hi",
"language:id",
"language:it",
"language:ja",
"language:ko",
"language:pt",
"language:sw",
"language:yo",
"language:zh",
"license:mit",
"size_categories:100K... | 100K<n<1M | 11,797 | null | 393,176 | 124,875,074 | [
"2009.03300"
] |
# Multilingual Massive Multitask Language Understanding (MMMLU)
The MMLU is a widely recognized benchmark of general knowledge attained by AI models. It covers a broad range of topics from 57 different categories, covering elementary-level knowledge up to advanced professional subjects like law, physics, history, and... |
dataset | meta-agents-research-environments/gaia2-cli | meta-agents-research-environments | 2026-04-09 | 2026-04-13 | [] | null | [] | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"region:us"
] | 1K<n<10K | 11,926 | null | 1,600 | 494,386,665 | [] |
# GAIA2 CLI
Benchmark dataset for [gaia2-cli](https://github.com/meta-agents-research-environments/gaia2-cli), the CLI-based agent evaluation harness.
## Schema
Each row has two columns:
| Column | Type | Description |
|--------|------|-------------|
| `scenario_id` | string | Unique scenario identifier (e.g. `sce... |
dataset | metimer/us_flight_data | metimer | 2026-02-12 | 2026-02-16 | [
"en"
] | apache-2.0 | [
"feature-extraction"
] | [
"task_categories:feature-extraction",
"language:en",
"license:apache-2.0",
"size_categories:100M<n<1B",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"region:us"
] | 100M<n<1B | 11,845 | null | 112,313,601 | 9,042,208,736 | [] | |
dataset | yanyan666/SpeechEval | yanyan666 | 2026-05-20 | 2026-05-20 | [
"en",
"zh",
"ja",
"fr"
] | cc-by-nc-sa-4.0 | [] | [
"language:en",
"language:zh",
"language:ja",
"language:fr",
"license:cc-by-nc-sa-4.0",
"size_categories:100K<n<1M",
"modality:audio",
"modality:text",
"arxiv:2510.14664",
"region:us",
"speech",
"quality",
"audio",
"evaluation",
"tts"
] | 100K<n<1M | 12,289 | null | 191,046 | 4,959,731,373 | [
"2510.14664"
] |
# SpeechEval
[](https://arxiv.org/abs/2510.14664)
[](https://creativecommons.org/licenses/by-nc-sa/4.0/)
[![Github](https://img.shields.io/badge/Github... |
dataset | commul/universal_dependencies | commul | 2025-08-01 | 2026-05-28 | [
"abq",
"ab",
"af",
"akk",
"aqz",
"sq",
"gsw",
"am",
"grc",
"hbo",
"apu",
"ar",
"hy",
"as",
"aii",
"az",
"bm",
"eu",
"bar",
"bej",
"be",
"bn",
"bho",
"sab",
"bor",
"brh",
"br",
"bg",
"bxr",
"yue",
"cpg",
"ca",
"ceb",
"ckb",
"zh",
"ctn",
"ckt",
... | apache-2.0 | [
"token-classification"
] | [
"task_categories:token-classification",
"task_ids:parsing",
"task_ids:part-of-speech",
"task_ids:lemmatization",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"multilinguality:multilingual",
"source_datasets:original",
"language:abq",
"language:ab",
"language:af",
... | 1K<n<10K | 11,898 | [
"multilingual"
] | 2,221,815 | 728,482,536 | [
"2004.10643"
] |
## Dataset Card (v2.0) for Universal Dependencies Treebank
**Version 2.0.0** introduces significant improvements and breaking changes:
- **Parquet Format:** faster loading with HuggingFace datasets >=4.0.0
- **MWT Support:** New `mwt` field provides structured multi-word token information
- **Enhanced Security:** No ... |
dataset | neh7777/Pretraining-V1 | neh7777 | 2026-05-15 | 2026-05-15 | [
"hi",
"bn",
"ta",
"te",
"mr",
"gu",
"kn",
"ml",
"pa",
"or",
"ur",
"as",
"sa",
"en",
"ne",
"doi",
"kok",
"mai",
"ug",
"ar",
"de",
"fr",
"es",
"it",
"nl",
"tr",
"ru",
"pt",
"pl"
] | cc-by-4.0 | [
"text-to-speech",
"automatic-speech-recognition"
] | [
"task_categories:text-to-speech",
"task_categories:automatic-speech-recognition",
"language:hi",
"language:bn",
"language:ta",
"language:te",
"language:mr",
"language:gu",
"language:kn",
"language:ml",
"language:pa",
"language:or",
"language:ur",
"language:as",
"language:sa",
"language... | 10M<n<100M | 12,075 | null | 16,172,757 | 7,891,002,747,800 | [] |
# Indic TTS Unified v1
A large-scale, unified collection of speech data for text-to-speech (TTS) and speech research. This dataset consolidates 17 distinct source datasets into a single, schema-normalized resource covering Indian / South Asian languages, plus major European, African, MENA, and Central Asian languages... |
dataset | agibot-world/AgiBotWorld-Alpha | agibot-world | 2024-12-19 | 2025-09-29 | [
"en"
] | null | [
"robotics",
"other"
] | [
"task_categories:robotics",
"task_categories:other",
"language:en",
"size_categories:10M<n<100M",
"format:webdataset",
"modality:text",
"library:datasets",
"library:webdataset",
"library:mlcroissant",
"region:us",
"real-world",
"dual-arm",
"Robotics manipulation"
] | 10M<n<100M | 11,952 | null | null | 9,664,486,530,289 | [] |
<!-- <img src="assets/agibot_world.gif" alt="Image Alt Text" width="70%" style="display: block; margin-left: auto; margin-right: auto;" /> -->
<video controls autoplay loop muted src="https://cdn-uploads.huggingface.co/production/uploads/6763e2cfd3c85f9b6d828f6c/9HkLtnqI_Qx62dNLLsI2I.mp4"></video>
<div align="center... |
dataset | clue/clue | clue | 2022-03-02 | 2024-01-17 | [
"zh"
] | unknown | [
"text-classification",
"multiple-choice"
] | [
"task_categories:text-classification",
"task_categories:multiple-choice",
"task_ids:topic-classification",
"task_ids:semantic-similarity-scoring",
"task_ids:natural-language-inference",
"task_ids:multiple-choice-qa",
"annotations_creators:other",
"language_creators:other",
"multilinguality:monolingu... | 100K<n<1M | 11,863 | [
"monolingual"
] | 797,130 | 298,246,299 | [
"2004.05986"
] |
# Dataset Card for "clue"
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
-... |
dataset | cc-clean/CC-MAIN-2017-09 | cc-clean | 2025-01-25 | 2025-01-25 | [] | null | [] | [
"size_categories:100M<n<1B",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | 100M<n<1B | 11,870 | null | 101,555,984 | 67,079,868,329 | [] | |
dataset | ericktwo/MMFineReason-Full-2.3M-Qwen3-VL-235B-Thinking | ericktwo | 2026-02-04 | 2026-02-04 | [
"en"
] | apache-2.0 | [
"visual-question-answering",
"question-answering",
"text-generation"
] | [
"task_categories:visual-question-answering",
"task_categories:question-answering",
"task_categories:text-generation",
"language:en",
"license:apache-2.0",
"size_categories:1M<n<10M",
"modality:image",
"modality:text",
"arxiv:2601.21821",
"region:us",
"multimodal",
"reasoning",
"chain-of-thou... | 1M<n<10M | 11,879 | null | 2,286,130 | 83,789,382,519 | [
"2601.21821"
] |
<div align="center">
<h1>MMFineReason-Full-2.3M</h1>
<p><strong>The Complete Pre-Selection Dataset — Before Quality Filtering</strong></p>
</div>
<div align="center">
[](https://arxiv.org/abs/2601.xxxxx)
[![Homepage](https://img.shields.io/badge/Homepage-MMFi... |
dataset | axolotl-ai-co/evolkit-logprobs-pipeline-75k-v2-sample | axolotl-ai-co | 2025-01-08 | 2025-01-08 | [] | null | [] | [
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | n<1K | 11,768 | null | 742 | 351,768,776 | [] | |
dataset | open-r1/codeforces | open-r1 | 2025-02-12 | 2025-05-19 | [] | cc-by-4.0 | [] | [
"license:cc-by-4.0",
"size_categories:10K<n<100K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | 10K<n<100K | 11,880 | null | 29,286 | 243,838,668,917 | [] | # Dataset Card for CodeForces
## Dataset description
[CodeForces](https://codeforces.com/) is one of the most popular websites among competitive programmers, hosting regular contests where participants must solve challenging algorithmic optimization problems. The challenging nature of these problems makes them an inte... |
dataset | mlfoundations/MINT-1T-PDF-CC-2023-14 | mlfoundations | 2024-07-12 | 2024-09-19 | [
"en"
] | cc-by-4.0 | [
"image-to-text",
"text-generation"
] | [
"task_categories:image-to-text",
"task_categories:text-generation",
"language:en",
"license:cc-by-4.0",
"size_categories:1M<n<10M",
"format:webdataset",
"modality:image",
"modality:text",
"library:datasets",
"library:webdataset",
"library:mlcroissant",
"arxiv:2406.11271",
"region:us",
"mul... | 1M<n<10M | 12,595 | null | 3,100 | 3,445,913,573,869 | [
"2406.11271"
] |
<h1 align="center">
🍃 MINT-1T:<br>Scaling Open-Source Multimodal Data by 10x:<br> A Multimodal Dataset with One Trillion Tokens
</h1>
🍃 MINT-1T is an open-source **M**ultimodal **INT**erleaved dataset with 1 trillion text tokens and 3.4 billion images, a 10x scale-up from existing open-source datasets. Additional... |
dataset | anonymous2222/Sympatheia-18k | anonymous2222 | 2026-04-30 | 2026-05-07 | [
"en"
] | cc-by-4.0 | [
"audio-to-audio",
"text-to-speech",
"audio-text-to-text"
] | [
"task_categories:audio-to-audio",
"task_categories:text-to-speech",
"task_categories:audio-text-to-text",
"language:en",
"license:cc-by-4.0",
"size_categories:10K<n<100K",
"format:json",
"modality:audio",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcro... | 10K<n<100K | 11,998 | null | 17,982 | 39,496,970,515 | [] |
# Sympatheia-18k
Sympatheia-18k is an emotion-aware spoken dialogue dataset for empathetic speech synthesis research.
It contains 18,000 query–response pairs across 12 emotion categories, each accompanied by
synthesized audio and text transcripts.
## Dataset Structure
| Subset | Unique Queries | Responses | Descrip... |
dataset | yifishbossman/financial-analyst-data-lite | yifishbossman | 2026-05-24 | 2026-05-24 | [
"zh",
"en"
] | apache-2.0 | [
"time-series-forecasting",
"tabular-classification"
] | [
"task_categories:time-series-forecasting",
"task_categories:tabular-classification",
"language:zh",
"language:en",
"license:apache-2.0",
"size_categories:1M<n<10M",
"format:text",
"modality:text",
"library:datasets",
"library:mlcroissant",
"region:us",
"finance",
"a-share",
"chinese-stocks... | 1M<n<10M | 12,110 | null | 8,015,046 | 3,292,277,601 | [] |
# financial-analyst-data-lite
> **EN**: A-share historical OHLCV + valuation + financials + TDX F10 events, packaged in Qlib binary + Parquet formats. Companion dataset for [**financial-analyst**](https://github.com/jesson-hh/financial-analyst) — a 14-agent single-stock deep-dive research workstation.
>
> **中文**... |
dataset | mlfoundations/MINT-1T-PDF-CC-2024-10 | mlfoundations | 2024-07-12 | 2024-09-19 | [
"en"
] | cc-by-4.0 | [
"image-to-text",
"text-generation"
] | [
"task_categories:image-to-text",
"task_categories:text-generation",
"language:en",
"license:cc-by-4.0",
"size_categories:1M<n<10M",
"format:webdataset",
"modality:image",
"modality:text",
"library:datasets",
"library:webdataset",
"library:mlcroissant",
"arxiv:2406.11271",
"region:us",
"mul... | 1M<n<10M | 12,464 | null | 3,400 | 7,513,049,235,948 | [
"2406.11271"
] |
<h1 align="center">
🍃 MINT-1T:<br>Scaling Open-Source Multimodal Data by 10x:<br> A Multimodal Dataset with One Trillion Tokens
</h1>
🍃 MINT-1T is an open-source **M**ultimodal **INT**erleaved dataset with 1 trillion text tokens and 3.4 billion images, a 10x scale-up from existing open-source datasets. Additional... |
dataset | ChilleD/StrategyQA | ChilleD | 2023-05-08 | 2023-08-26 | [] | mit | [] | [
"license:mit",
"size_categories:1K<n<10K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | 1K<n<10K | 11,677 | null | 2,290 | 1,123,205 | [] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.