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 โ | num_dataset_rows float64 0 194B โ | disk_size float64 6 306,846B โ | arxiv_ids listlengths 0 440 | readme large_stringlengths 0 13.4M |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
dataset | NuTonic/sat-image-boundingbox-sft-large | NuTonic | 2026-04-23 | 2026-04-23 | [] | apache-2.0 | [] | [
"license:apache-2.0",
"size_categories:100K<n<1M",
"format:json",
"modality:image",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"region:us"
] | 100K<n<1M | 21,714 | null | 531,408 | 74,682,612,680 | [] | |
dataset | gaianet/none | gaianet | 2024-04-28 | 2024-05-04 | [] | apache-2.0 | [] | [
"license:apache-2.0",
"size_categories:n<1K",
"format:webdataset",
"modality:text",
"library:datasets",
"library:webdataset",
"library:mlcroissant",
"region:us"
] | n<1K | 18,453 | null | 1 | 76,042,915 | [] |
An empty snapshot was generated by all-MiniLM-L6-v2-ggml-model-f16.gguf and the Qdrant vector DB. |
dataset | gmongaras/CC12M_and_Imagenet21K_Recap | gmongaras | 2025-02-03 | 2025-09-17 | [] | null | [] | [
"size_categories:10M<n<100M",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | 10M<n<100M | 19,144 | null | 22,682,920 | 4,342,103,655,745 | [] |
I removed all low quality data and uploaded it [here](https://huggingface.co/datasets/gmongaras/CC12M_and_Imagenet21K_Recap_Highqual)
This dataset is the entire 21K ImageNet dataset with about 13 million examples and about 19 thousand classes as strings
(for some reason it only had ~19K classes instead of 21K) as we... |
dataset | bagadbilla/amazon-reviews-2023-trimmed | bagadbilla | 2025-06-18 | 2025-06-18 | [
"en"
] | other | [
"text-classification"
] | [
"task_categories:text-classification",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"source_datasets:Julian McAuley et al., 2023",
"language:en",
"license:other",
"size_categories:100M<n<1B",
"format:parquet",
"modality:text",
"library:datasets"... | 100M<n<1B | 18,644 | [
"monolingual"
] | 571,544,897 | 85,359,064,741 | [
"2403.03952"
] |
# Amazon Product Reviews 2023 (Trimmed, 34 Categories)
This dataset is a **trimmed and restructured** version of the [Amazon Product Reviews 2023 dataset](https://amazon-reviews-2023.github.io/index.html) by Julian McAuley and the UCSD Computer Science department.
It includes **34 product categories**, each stored a... |
dataset | Tevatron/browsecomp-plus | Tevatron | 2025-08-08 | 2025-12-20 | [] | mit | [
"question-answering"
] | [
"task_categories:question-answering",
"license:mit",
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2508.06600",
"region:us",
"retrieval-augmented-generation",
"rag",
"benchmark",
"llm",
"in... | n<1K | 18,364 | null | 830 | 2,781,436,779 | [
"2508.06600"
] |
# BrowseComp-Plus
BrowseComp-Plus is a new benchmark for Deep-Research system, isolating the effect of the retriever and the LLM agent to enable **fair, transparent comparisons of Deep-Research agents**. The benchmark sources challenging, reasoning-intensive queries from OpenAI's [BrowseComp](https://openai.com/index... |
dataset | argilla/distilabel-capybara-dpo-7k-binarized | argilla | 2024-01-26 | 2024-07-16 | [
"en"
] | apache-2.0 | [
"question-answering",
"text-generation"
] | [
"task_categories:question-answering",
"task_categories:text-generation",
"language:en",
"license:apache-2.0",
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"library:distilabel"... | 1K<n<10K | 18,370 | null | 7,563 | 155,790,036 | [] | # Capybara-DPO 7K binarized
> A DPO dataset built with [distilabel](https://github.com/argilla-io/distilabel) atop the awesome [LDJnr/Capybara](https://huggingface.co/datasets/LDJnr/Capybara)
> This is a preview version to collect feedback from the community. v2 will include the full base dataset and responses from m... |
dataset | yangzekang2000/CORAL | yangzekang2000 | 2026-04-20 | 2026-05-10 | [] | cc-by-4.0 | [
"image-segmentation",
"image-to-text"
] | [
"task_categories:image-segmentation",
"task_categories:image-to-text",
"license:cc-by-4.0",
"size_categories:1K<n<10K",
"format:text",
"modality:image",
"modality:text",
"library:datasets",
"library:mlcroissant",
"region:us",
"neuroscience",
"neuron-reconstruction",
"neuron-tracing",
"brai... | 1K<n<10K | 19,137 | null | 1,929 | 4,423,623,049,572 | [] | CORAL is the dataset for **CORAL: A Benchmark for Structure-aware and Brain-wide Neuron Reconstruction in Light Microscopy**.
The benchmark contains data for two neuron reconstruction settings:
- **Block-level reconstruction**: reconstruct local neuron morphology from small 3D image blocks.
- **Brain-wide reconstruct... |
dataset | js-astro/gaia-dr3-tmass-allwise-600K | js-astro | 2025-04-26 | 2025-04-26 | [] | null | [] | [
"size_categories:100K<n<1M",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | 100K<n<1M | 18,363 | null | 594,426 | 136,625,628 | [] | |
dataset | anon-cmevs-2026/cmevs-erp-eval | anon-cmevs-2026 | 2026-05-03 | 2026-05-09 | [
"en"
] | other | [
"depth-estimation",
"image-to-image"
] | [
"task_categories:depth-estimation",
"task_categories:image-to-image",
"language:en",
"license:other",
"size_categories:n<1K",
"format:csv",
"modality:image",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"region:us",
"... | n<1K | 20,156 | null | 1 | 116,885,234,509 | [] |
# CM-EVS: A Coverage-Curated Panoramic RGB-D Dataset for Indoor Scene Understanding
CM-EVS is a curated panoramic RGB-D dataset built under a single principle: **maximize the geometric coverage of a 3D scene with the fewest equirectangular (ERP) frames possible**. The release is structured as one redistributable Blen... |
dataset | novelwolde36/WaxalNLP | novelwolde36 | 2026-02-19 | 2026-02-19 | [
"ach",
"aka",
"amh",
"dag",
"dga",
"ewe",
"fat",
"ful",
"hau",
"ibo",
"kik",
"kpo",
"lin",
"lug",
"luo",
"mas",
"mlg",
"nyn",
"orm",
"sid",
"sna",
"sog",
"swa",
"tir",
"twi",
"wal",
"yor"
] | cc-by-sa-4.0 | [
"automatic-speech-recognition",
"text-to-speech"
] | [
"task_categories:automatic-speech-recognition",
"task_categories:text-to-speech",
"language_creators:creator_1",
"multilinguality:multilingual",
"source_datasets:UGSpeechData",
"source_datasets:DigitalUmuganda/AfriVoice",
"source_datasets:original",
"language:ach",
"language:aka",
"language:amh",
... | 1M<n<10M | 18,381 | [
"multilingual"
] | 2,553,545 | 799,101,967,634 | [
"2602.02734"
] |
# Waxal Datasets
The WAXAL dataset is a large-scale multilingual speech corpus for African languages, introduced in the paper [WAXAL: A Large-Scale Multilingual African Language Speech Corpus](https://huggingface.co/papers/2602.02734).
## Table of Contents
- [Dataset Description](#dataset-description)
- [AS... |
dataset | llamafactory/v1-sft-demo | llamafactory | 2025-10-08 | 2025-12-11 | [] | apache-2.0 | [] | [
"license:apache-2.0",
"size_categories:n<1K",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | n<1K | 18,314 | null | 500 | 446,660 | [] | |
dataset | RuoliuYang/ULVR_all | RuoliuYang | 2026-05-16 | 2026-05-20 | [
"en"
] | null | [] | [
"language:en",
"size_categories:10K<n<100K",
"modality:image",
"modality:text",
"region:us",
"image",
"multimodal",
"reasoning",
"visual-question-answering",
"synthetic"
] | 10K<n<100K | 19,874 | null | 53,106 | 109,389,235,627 | [] | ## Full Monet training data (compressed)
Loose files under `images/` on this repo are **incomplete** (Hub directory file limit). Download and extract:
| Archive | Contents |
|---------|----------|
| `archives/monet_train.tar.zst` | `no_text/train.jsonl` |
| `archives/images_input.tar.zst` | `images/input/` |
| `archi... |
dataset | bigcode/github-commits-diff-dedup-pjjs-april | bigcode | 2023-04-16 | 2023-04-17 | [] | null | [] | [
"size_categories:100K<n<1M",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | 100K<n<1M | 18,356 | null | 146,054 | 182,470,375,664 | [] | # Deduplicated Commits
Deduplicated based on diff:
```
content = '\n'.join(difflib.unified_diff(
old_content.splitlines(keepends=True),
new_content.splitlines(keepends=True),
n=5
))
```
## Parameters:
Minimum ngram size: 5
MinHash ngram size: 5
MinHash threshold: 0.8 |
dataset | allenai/Molmo2-ER-VST-P | allenai | 2026-05-05 | 2026-05-05 | [
"en"
] | cc-by-nc-4.0 | [] | [
"language:en",
"license:cc-by-nc-4.0",
"size_categories:100K<n<1M",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"arxiv:2511.05491",
"region:us",
"embodied-reasoning",
"molmo2",
"molmo2-er",
"vlm-training-data"
] | 100K<n<1M | 18,277 | null | 563,190 | 504,873,020,837 | [
"2511.05491"
] |
# Molmo2-ER ยท rayruiyang/vst_500k
500K perception QA over images normalized to a uniform virtual camera (single + multi-view).
This is a re-hosted, **loader-ready subset** of the upstream dataset, used to train [`allenai/Molmo2-ER-4B`](https://huggingface.co/allenai/Molmo2-ER-4B). Files mirror the upstream layout; n... |
dataset | macrolens/MacroLens | macrolens | 2026-05-04 | 2026-05-20 | [
"en"
] | cc-by-4.0 | [
"time-series-forecasting",
"tabular-regression",
"text-generation",
"question-answering"
] | [
"task_categories:time-series-forecasting",
"task_categories:tabular-regression",
"task_categories:text-generation",
"task_categories:question-answering",
"language:en",
"license:cc-by-4.0",
"size_categories:10M<n<100M",
"format:parquet",
"modality:document",
"modality:tabular",
"modality:text",
... | 10M<n<100M | 20,815 | null | 10,530,303 | 17,024,405,850 | [] |
# MacroLens
A benchmarking corpus for **contextual financial reasoning under macroeconomic scenarios** across **4,416 U.S. small- and micro-cap equities (2021-01-04 โ 2026-03-31)**. MacroLens unifies seven tasks over a single point-in-time panel: contextual time-series forecasting, public valuation, financial-stateme... |
dataset | obss/ai-intern-challenge-2025 | obss | 2025-05-25 | 2025-05-26 | [] | cc-by-sa-4.0 | [] | [
"license:cc-by-sa-4.0",
"size_categories:10K<n<100K",
"format:csv",
"modality:image",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | 10K<n<100K | 18,190 | null | 25,138 | 1,046,174,653 | [] | |
dataset | mythicinfinity/libritts_r | mythicinfinity | 2024-02-03 | 2024-02-09 | [
"en"
] | cc-by-4.0 | [
"text-to-speech"
] | [
"task_categories:text-to-speech",
"language:en",
"license:cc-by-4.0",
"size_categories:100K<n<1M",
"format:parquet",
"modality:audio",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2305.18802",
"region:us"
] | 100K<n<1M | 18,099 | null | 755,734 | 100,550,721,966 | [
"2305.18802"
] | # Dataset Card for LibriTTS-R
<!-- Provide a quick summary of the dataset. -->
LibriTTS-R [1] is a sound quality improved version of the LibriTTS corpus
(http://www.openslr.org/60/) which is a multi-speaker English corpus of approximately
585 hours of read English speech at 24kHz sampling rate, published in 2019.
... |
dataset | iNeil77/HumanEval-XL | iNeil77 | 2024-09-15 | 2024-09-15 | [] | null | [
"text-generation"
] | [
"task_categories:text-generation",
"size_categories:10K<n<100K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us",
"code"
] | 10K<n<100K | 18,106 | null | 20,240 | 19,556,974 | [] |
This dataset contains a viewer-friendly version of the dataset at `FloatAI/HumanEval-XL`. It is made available separately for the convenience of the [vllm-code-harness](https://github.com/iNeil77/vllm-code-harness) package.
|
dataset | lightonai/cornstack | lightonai | 2025-11-26 | 2026-02-12 | [
"en",
"code"
] | apache-2.0 | [] | [
"language:en",
"language:code",
"license:apache-2.0",
"size_categories:10M<n<100M",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"arxiv:2412.01007",
"region:eu"
] | 10M<n<100M | 18,268 | null | 21,502,474 | 451,010,101,149 | [
"2412.01007"
] |
This dataset is a copy of the [CoRNStack data](https://huggingface.co/collections/nomic-ai/cornstack) from Nomic. This is just a reformating of the data to make it easily usable in [PyLate](https://lightonai.github.io/pylate/) and [sentence-transformers](https://github.com/huggingface/sentence-transformers). The data ... |
dataset | benchmark-anon-2026/RoadmapBench | benchmark-anon-2026 | 2026-05-06 | 2026-05-07 | [
"en"
] | mit | [
"text-generation"
] | [
"task_categories:text-generation",
"language:en",
"license:mit",
"size_categories:n<1K",
"format:json",
"modality:image",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"region:us",
"code-generation",
"software-engineering",
"benchmark",
... | n<1K | 19,356 | null | 115 | 1,350,832,472 | [] |
# RoadmapBench
A benchmark for evaluating AI coding agents on multi-target, long-horizon software development tasks derived from open-source project version upgrades.
## Overview
RoadmapBench contains 115 tasks spanning 17 open-source repositories across 5 programming languages (Python, TypeScript, Go, Rust, C++). ... |
dataset | moondream/megalith-mdqa | moondream | 2024-10-18 | 2025-03-30 | [] | openrail | [
"question-answering"
] | [
"task_categories:question-answering",
"license:openrail",
"size_categories:1M<n<10M",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | 1M<n<10M | 18,205 | null | 5,463,341 | 1,833,458,332,388 | [] |
Images from Megalith, synthetically captioned using Moondream, with the questions then transformed to short-form QA using an LLM. |
dataset | bigcode/the-stack | bigcode | 2022-10-03 | 2023-04-13 | [
"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 | 18,383 | [
"multilingual"
] | null | 2,452,779,784,682 | [
"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 | edinburgh-dawg/mmlu-redux-2.0 | edinburgh-dawg | 2024-08-17 | 2025-02-25 | [
"en"
] | cc-by-4.0 | [
"question-answering"
] | [
"task_categories:question-answering",
"language:en",
"license:cc-by-4.0",
"size_categories:1K<n<10K",
"format:arrow",
"modality:text",
"library:datasets",
"library:mlcroissant",
"arxiv:2502.03461",
"arxiv:2406.04127",
"doi:10.57967/hf/3469",
"region:us"
] | 1K<n<10K | 18,074 | null | 5,700 | 2,904,914 | [
"2502.03461",
"2406.04127"
] |
# Dataset Card for MMLU-Redux-2.0
<!-- Provide a quick summary of the dataset. -->
MMLU-Redux is a subset of 5,700 manually re-annotated questions across 57 MMLU subjects.
## News
- [2025.02.25] We corrected one annotation in Abstract Algebra subset, as noted in the Issue [#2](https://huggingface.co/datasets/edin... |
dataset | bigcode/the-stack-v2 | bigcode | 2024-02-26 | 2024-04-23 | [
"code"
] | other | [
"text-generation"
] | [
"task_categories:text-generation",
"language_creators:crowdsourced",
"language_creators:expert-generated",
"multilinguality:multilingual",
"language:code",
"license:other",
"size_categories:1B<n<10B",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
... | 1B<n<10B | 18,014 | [
"multilingual"
] | null | 839,609,928,672 | [
"2402.19173",
"2107.03374",
"2207.14157"
] |
# The Stack v2
<center>
<img src="https://huggingface.co/datasets/bigcode/admin_private/resolve/main/thestackv2_banner.png" alt="Stackv2" width="900" height="600">
</center>
## Dataset Description
- **Homepage:** https://www.bigcode-project.org/
- **Repository:** https://github.com/bigcode-project
- **Paper:** ... |
dataset | sparklabutah/TimeWarp-GPT5-Traces | sparklabutah | 2026-03-08 | 2026-03-08 | [] | mit | [] | [
"license:mit",
"modality:image",
"modality:text",
"region:us"
] | null | 18,994 | null | null | 1,850,970,670 | [] | |
dataset | HuggingFaceGECLM/StackExchange_Mar2023 | HuggingFaceGECLM | 2023-03-13 | 2023-03-16 | [] | null | [] | [
"size_categories:10M<n<100M",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | 10M<n<100M | 17,898 | null | 19,396,405 | 52,712,238,428 | [] | # Dataset Card for "StackExchange_Mar2023"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
dataset | allenai/tulu-3-sft-olmo-2-mixture-0225 | allenai | 2025-02-21 | 2025-03-14 | [] | null | [] | [
"size_categories:100K<n<1M",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | 100K<n<1M | 17,799 | null | 866,138 | 1,265,033,853 | [] |
Used to train OLMo 2 32B. From the [blog post](https://allenai.org/blog/olmo2-32B):
> Filtered out instructions from the SFT dataset and the chosen responses of the preference data that included mentions of a date cutoff from the synthetic data generation process. This resulted in a new version of the instruction data... |
dataset | SpatialVID/SpatialVID | SpatialVID | 2025-09-08 | 2026-03-24 | [
"en"
] | cc-by-nc-sa-4.0 | [
"text-to-video",
"text-to-3d",
"image-to-3d",
"image-to-video",
"other"
] | [
"task_categories:text-to-video",
"task_categories:text-to-3d",
"task_categories:image-to-3d",
"task_categories:image-to-video",
"task_categories:other",
"language:en",
"license:cc-by-nc-sa-4.0",
"size_categories:1M<n<10M",
"format:csv",
"modality:tabular",
"modality:text",
"library:datasets",
... | 1M<n<10M | 17,736 | null | null | 7,667,890,305,402 | [
"2509.09676"
] | <h1 align='center'>SpatialVID: A Large-Scale Video Dataset with Spatial Annotations</h1>
<div align='center'>
<a href='https://oiiiwjh.github.io/' target='_blank'>Jiahao Wang</a><sup>1*</sup>โ
<a href='https://FelixYuan-YF.github.io/' target='_blank'>Yufeng Yuan</a><sup>1*</sup>โ
<a href='https://github.com... |
dataset | stereo-dataset/stereo-dataset | stereo-dataset | 2026-05-02 | 2026-05-20 | [
"en"
] | cc-by-4.0 | [
"depth-estimation"
] | [
"task_categories:depth-estimation",
"language:en",
"license:cc-by-4.0",
"size_categories:n<1K",
"format:parquet",
"format:optimized-parquet",
"modality:image",
"modality:text",
"modality:timeseries",
"modality:video",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcrois... | n<1K | 20,595 | null | 21 | 763,754,523,419 | [] |
# Stereo Dataset
## Dataset Summary
StereoDataset is a synthetic multiview stereo dataset rendered in Unreal Engine.
Each scene combines a map, a character mesh, an animation clip, a validated
spawn location, and a camera trajectory. The released scene folders contain
synchronized per-camera RGB videos (`cam_XX_rgb.... |
dataset | SparkAudio/voxbox | SparkAudio | 2025-04-07 | 2025-04-15 | [
"zh",
"en"
] | cc-by-nc-sa-4.0 | [
"text-to-speech"
] | [
"task_categories:text-to-speech",
"language:zh",
"language:en",
"license:cc-by-nc-sa-4.0",
"size_categories:10M<n<100M",
"format:webdataset",
"modality:audio",
"modality:text",
"library:datasets",
"library:webdataset",
"library:mlcroissant",
"arxiv:2503.01710",
"region:us",
"speech",
"au... | 10M<n<100M | 17,674 | null | 17,300 | 4,838,398,404,422 | [
"2503.01710"
] |
# VoxBox
This dataset is a curated collection of bilingual speech corpora annotated clean transcriptions and rich metadata incluing age, gender, and emotion.
## Dataset Structure
```bash
.
โโโ audios/
โ โโโ aishell-3/ # Audio files (organised by sub-corpus)
โ โโโ ...
โโโ metadata/
โโโ a... |
dataset | krafton-seungjin/terminal-bench-2-leaderboard | krafton-seungjin | 2026-02-12 | 2026-02-12 | [] | apache-2.0 | [] | [
"license:apache-2.0",
"modality:text",
"region:us"
] | null | 18,884 | null | null | 4,639,509,108 | [] |
# Terminal-Bench 2.0 Leaderboard Submissions
This repository accepts leaderboard submissions for [Terminal-Bench 2.0](https://terminal-bench.org).
## How to Submit
1. [Fork this repository](https://huggingface.co/docs/hub/en/repositories-next-steps#duplicating-with-the-git-history-fork)
2. Create a new bran... |
dataset | lhoestq/test2 | lhoestq | 2022-03-02 | 2021-07-23 | [] | null | [] | [
"size_categories:n<1K",
"format:text",
"modality:text",
"library:datasets",
"library:mlcroissant",
"region:us"
] | n<1K | 17,581 | null | 20 | 787 | [] | This is a readme
|
dataset | PrimeIntellect/fineweb-edu | PrimeIntellect | 2024-10-07 | 2024-10-16 | [
"en"
] | odc-by | [] | [
"language:en",
"license:odc-by",
"size_categories:1B<n<10B",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | 1B<n<10B | 18,023 | null | 1,198,800,000 | 3,395,660,966,177 | [] |
# Pre-shuffled [fineweb-edu](https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu) dataset
|
dataset | allenai/WildChat-1M | allenai | 2024-05-03 | 2024-10-17 | [] | odc-by | [
"text-generation",
"question-answering",
"text2text-generation"
] | [
"task_categories:text-generation",
"task_categories:question-answering",
"license:odc-by",
"size_categories:100K<n<1M",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2405.01470",
"arxiv:2409.03753",
"arxiv:2406.13706",
... | 100K<n<1M | 17,627 | null | 837,989 | 3,360,869,442 | [
"2405.01470",
"2409.03753",
"2406.13706"
] | # Dataset Card for WildChat
## Dataset Description
- **Paper:** https://arxiv.org/abs/2405.01470
- **Interactive Search Tool:** https://wildvisualizer.com ([paper](https://arxiv.org/abs/2409.03753))
- **License:** [ODC-BY](https://opendatacommons.org/licenses/by/1-0/)
- **Language(s) (NLP):** multi-lingual
- **P... |
dataset | TrevorDohm/Stack_Tokenized | TrevorDohm | 2024-03-10 | 2024-04-16 | [
"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:text",
"library:datasets",
"library:dask",
"library:mlcroissant"... | 100M<n<1B | 18,404 | [
"multilingual"
] | 545,547,422 | 2,737,604,000,396 | [] | |
dataset | BangumiBase/saikyounoousamanidomenojinseiwananiwosuru | 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 | 17,581 | null | null | 11,520,642,085 | [] |
# Bangumi Image Base of Saikyou No Ousama, Nidome No Jinsei Wa Nani Wo Suru?
This is the image base of bangumi Saikyou no Ousama, Nidome no Jinsei wa Nani wo Suru?, we detected 71 characters, 4913 images in total. The full dataset is [here](all.zip).
**Please note that these image bases are not guaranteed to be 100%... |
dataset | chenzeyang1/datasets | chenzeyang1 | 2026-05-08 | 2026-05-13 | [] | mit | [] | [
"license:mit",
"size_categories:1K<n<10K",
"format:imagefolder",
"modality:image",
"modality:text",
"library:datasets",
"library:mlcroissant",
"region:us"
] | 1K<n<10K | 20,255 | null | 4,347 | 102,935,671,713 | [] | |
dataset | TIGER-Lab/OmniEdit-Filtered-1.2M | TIGER-Lab | 2024-11-11 | 2024-12-06 | [
"en"
] | mit | [] | [
"language:en",
"license:mit",
"size_categories:1M<n<10M",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2411.07199",
"region:us",
"image"
] | 1M<n<10M | 17,501 | null | 1,203,497 | 2,978,260,325,353 | [
"2411.07199"
] |
## OmniEdit
In this paper, we present OMNI-EDIT, which is an omnipotent editor to handle seven different image editing tasks with any aspect ratio seamlessly. Our contribution is in four folds: (1) OMNI-EDIT is trained by utilizing the supervision
from seven different specialist models to ensure task coverage. (2) w... |
dataset | Helsinki-NLP/multiun | Helsinki-NLP | 2022-03-02 | 2024-02-27 | [
"ar",
"de",
"en",
"es",
"fr",
"ru",
"zh"
] | unknown | [
"translation"
] | [
"task_categories:translation",
"annotations_creators:found",
"language_creators:found",
"multilinguality:multilingual",
"source_datasets:original",
"language:ar",
"language:de",
"language:en",
"language:es",
"language:fr",
"language:ru",
"language:zh",
"license:unknown",
"size_categories:1... | 100M<n<1B | 17,453 | [
"multilingual"
] | 159,488,597 | 31,775,757,728 | [] |
# Dataset Card for OPUS MultiUN
## 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-instance... |
dataset | theforecastingcompany/GiftEvalPretrain | theforecastingcompany | 2025-10-08 | 2026-03-31 | [] | apache-2.0 | [
"time-series-forecasting"
] | [
"task_categories:time-series-forecasting",
"license:apache-2.0",
"size_categories:1M<n<10M",
"format:parquet",
"format:optimized-parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"arxiv:2407.18015",
"region:us",
"time-series",
"forecast... | 1M<n<10M | 17,822 | null | 6,964,617 | 878,264,402,202 | [
"2407.18015"
] |
# GiftEval Pretrain (Derived)
This dataset is a derived version of [Salesforce/GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain), the pre-training dataset aligned with the [GIFT-Eval](https://huggingface.co/datasets/Salesforce/GiftEval) benchmark for time series foundation models.
## Di... |
dataset | KRAFTON/terminal-bench-2-leaderboard | KRAFTON | 2026-02-12 | 2026-02-12 | [] | apache-2.0 | [] | [
"license:apache-2.0",
"modality:text",
"region:us"
] | null | 18,927 | null | null | 4,639,509,108 | [] |
# Terminal-Bench 2.0 Leaderboard Submissions
This repository accepts leaderboard submissions for [Terminal-Bench 2.0](https://terminal-bench.org).
## How to Submit
1. [Fork this repository](https://huggingface.co/docs/hub/en/repositories-next-steps#duplicating-with-the-git-history-fork)
2. Create a new bran... |
dataset | RichardChenZH/MedForge-90K | RichardChenZH | 2026-04-12 | 2026-04-12 | [
"en"
] | c-uda | [] | [
"language:en",
"license:c-uda",
"size_categories:10K<n<100K",
"format:text",
"modality:image",
"modality:text",
"library:datasets",
"library:mlcroissant",
"arxiv:2603.18577",
"region:us",
"medical",
"deepfake-detection",
"multimodal",
"reasoning",
"chest-xray",
"mri",
"fundus"
] | 10K<n<100K | 20,181 | null | 94,607 | 5,773,848,109 | [
"2603.18577"
] |
# MedForge-90K
**MedForge-90K** is a large-scale benchmark for **interpretable medical deepfake detection** under realistic **text-guided lesion editing** on authentic scans. It pairs **real clinical-style images** with **high-fidelity forged counterparts** (lesion **implant/edit** and **removal**), and provides *... |
dataset | antinomyhq/terminal-bench-2-leaderboard-1 | antinomyhq | 2026-02-21 | 2026-02-23 | [] | apache-2.0 | [] | [
"license:apache-2.0",
"modality:text",
"region:us"
] | null | 18,703 | null | null | 9,703,322,787 | [] |
# Terminal-Bench 2.0 Leaderboard Submissions
This repository accepts leaderboard submissions for [Terminal-Bench 2.0](https://terminal-bench.org).
## How to Submit
1. [Fork this repository](https://huggingface.co/docs/hub/en/repositories-next-steps#duplicating-with-the-git-history-fork)
2. Create a new bran... |
dataset | disco-eth/EuroSpeech-24kHz | disco-eth | 2025-06-19 | 2026-05-04 | [] | mit | [
"automatic-speech-recognition"
] | [
"task_categories:automatic-speech-recognition",
"license:mit",
"size_categories:10M<n<100M",
"format:parquet",
"modality:audio",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"arxiv:2510.00514",
"region:us"
] | 10M<n<100M | 17,514 | null | 13,391,074 | 2,609,621,697,909 | [
"2510.00514"
] |
# EuroSpeech 24 kHz Dataset
## Dataset Description
EuroSpeech is a large-scale multilingual speech corpus containing high-quality aligned parliamentary speech across 22 European languages. The dataset was constructed by processing parliamentary proceedings using a robust alignment pipeline that handles diverse audio... |
dataset | mythicinfinity/libriheavy | mythicinfinity | 2024-07-11 | 2026-04-02 | [
"en"
] | apache-2.0 | [
"text-to-speech",
"automatic-speech-recognition"
] | [
"task_categories:text-to-speech",
"task_categories:automatic-speech-recognition",
"language:en",
"license:apache-2.0",
"size_categories:10M<n<100M",
"format:parquet",
"modality:audio",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"arxiv:2309.0... | 10M<n<100M | 17,378 | null | 12,441,834 | 1,498,151,506,856 | [
"2309.08105"
] |
# Libriheavy
Libriheavy: a 50,000 hours ASR corpus with punctuation casing and context. Libriheavy is a labeled version of Librilight.
This uploaded version replaces the default Libri-Light audio files with the highest quality available versions
from librivox. In most cases, this consists an upgrade of the source au... |
dataset | Turki-Alshuaibi/haris-weapon-detection-dataset-curated | Turki-Alshuaibi | 2026-05-18 | 2026-05-18 | [] | cc-by-4.0 | [] | [
"license:cc-by-4.0",
"modality:image",
"modality:text",
"region:us"
] | null | 18,000 | null | null | 2,683,185,029 | [] | |
dataset | HAERAE-HUB/KMMLU | HAERAE-HUB | 2023-11-27 | 2024-03-05 | [
"ko"
] | cc-by-nd-4.0 | [
"multiple-choice"
] | [
"task_categories:multiple-choice",
"language:ko",
"license:cc-by-nd-4.0",
"size_categories:100K<n<1M",
"format:csv",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"arxiv:2402.11548",
"region:us",
"mmlu",
"haerae"
] | 100K<n<1M | 17,182 | null | 243,777 | 70,676,114 | [
"2402.11548"
] | # KMMLU (Korean-MMLU)
We propose KMMLU, a new Korean benchmark with 35,030 expert-level multiple-choice questions across 45 subjects ranging from humanities to STEM.
Unlike previous Korean benchmarks that are translated from existing English benchmarks, KMMLU is collected from original Korean exams, capturing linguis... |
dataset | DKYoon/SlimPajama-6B | DKYoon | 2023-08-21 | 2023-08-21 | [
"en"
] | null | [
"text-generation"
] | [
"task_categories:text-generation",
"language:en",
"size_categories:1M<n<10M",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | 1M<n<10M | 16,965 | null | 5,507,693 | 14,048,976,769 | [] | Sampled version of [cerebras/SlimPajama-627B](https://huggingface.co/datasets/cerebras/SlimPajama-627B).
[Since the original data was shuffled before chunking](https://huggingface.co/datasets/cerebras/SlimPajama-627B/discussions/4), I only downloaded train/chunk1 (of 10 total) and further sampled 10%. This should resu... |
dataset | ibm-granite/ChartNet | ibm-granite | 2026-03-17 | 2026-05-15 | [] | cdla-permissive-2.0 | [
"image-to-text",
"visual-question-answering",
"table-question-answering",
"text-generation"
] | [
"task_categories:image-to-text",
"task_categories:visual-question-answering",
"task_categories:table-question-answering",
"task_categories:text-generation",
"license:cdla-permissive-2.0",
"size_categories:1M<n<10M",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"librar... | 1M<n<10M | 17,215 | null | 4,938,028 | 829,790,394,570 | [
"2603.27064"
] | # ChartNet: A Million-Scale Multimodal Dataset for Chart Understanding
๐ [Homepage](https://huggingface.co/datasets/ibm-granite/ChartNet) | ๐ [arXiv](https://arxiv.org/abs/2603.27064)
---
## ๐ Changelog
- **May 15, 2026** โ Added link to [30K real-world charts and detailed captions dataset](https://huggingface.co... |
dataset | JQL-AI/hplt2_edu_scores | JQL-AI | 2025-07-29 | 2025-08-11 | [
"sq",
"bg",
"ca",
"cs",
"da",
"de",
"es",
"et",
"el",
"eu",
"fi",
"fr",
"gl",
"ga",
"hr",
"hu",
"hy",
"is",
"it",
"lv",
"lt",
"mk",
"nl",
"pl",
"pt",
"ro",
"sl",
"sk",
"sr",
"tr",
"sv",
"nb",
"nn"
] | null | [
"text-ranking"
] | [
"task_categories:text-ranking",
"language:sq",
"language:bg",
"language:ca",
"language:cs",
"language:da",
"language:de",
"language:es",
"language:et",
"language:el",
"language:eu",
"language:fi",
"language:fr",
"language:gl",
"language:ga",
"language:hr",
"language:hu",
"language:... | 1B<n<10B | 17,166 | null | 588,223,590 | 1,809,469,576,782 | [
"2505.22232"
] |
# HPLT2-Edu-scores
## Dataset summary
HPLT2-JQL-Education is a **model-annotated** language subset of [**HPLT2**](https://hplt-project.org/datasets/v2.0), spanning **35 languages**.
Our model-annotations allow for a filtering that achieves higher-quality training outcomes without excessively aggressive data reducti... |
dataset | ceselder/fineweb-loracle-loras-v1 | ceselder | 2026-04-08 | 2026-04-08 | [
"en"
] | mit | [] | [
"language:en",
"license:mit",
"size_categories:1K<n<10K",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"region:us",
"lora",
"peft",
"mechanistic-interpretability",
"loracle",
"gradient-oracles",
... | 1K<n<10K | 17,647 | null | 5,000 | 436,643,048,059 | [] |
# FineWeb gradient-oracles LoRAs (5000 ร randomly-hparamed continued-pretrain LoRAs on Qwen3-14B)
This dataset contains **5000 LoRA adapters trained on individual FineWeb documents** as part of the
**gradient-oracles** experiment in [ceselder/loracles](https://github.com/ceselder/loracles)
(branch `gradient-oracles`)... |
dataset | Brianpuz/terminal-bench-2-leaderboard | Brianpuz | 2026-03-03 | 2026-03-03 | [] | apache-2.0 | [] | [
"license:apache-2.0",
"modality:text",
"region:us"
] | null | 17,998 | null | null | 4,078,226,199 | [] |
# Terminal-Bench 2.0 Leaderboard Submissions
This repository accepts leaderboard submissions for [Terminal-Bench 2.0](https://terminal-bench.org).
## How to Submit
1. [Fork this repository](https://huggingface.co/docs/hub/en/repositories-next-steps#duplicating-with-the-git-history-fork)
2. Create a new bran... |
dataset | Intelligent-Internet/GAIA-Subset-Benchmark | Intelligent-Internet | 2025-03-28 | 2025-07-01 | [] | null | [] | [
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | n<1K | 16,926 | null | 44 | 357,924 | [] |
# GAIA Benchmark Subset Model Card
This dataset is a subset of the GAIA benchmark, containing 44 web-search-based questions from the validation set. It evaluates multiple AI models on their ability to retrieve and process real-time information using web search and browser tools. Performance metrics include success i... |
dataset | mlfoundations/datacomp_xlarge | mlfoundations | 2023-05-22 | 2023-08-21 | [] | cc-by-4.0 | [] | [
"license:cc-by-4.0",
"size_categories:10B<n<100B",
"format:parquet",
"modality:image",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | 10B<n<100B | 18,311 | null | 12,799,001,169 | 81,704,114,483,843 | [] |
## DataComp XLarge Pool
This repository contains metadata files for the xlarge pool of DataComp. For details on how to use the metadata, please visit [our website](https://www.datacomp.ai/) and our [github repository](https://github.com/mlfoundations/datacomp).
We distribute the image url-text samples and metadata u... |
dataset | HuggingFaceH4/ultrafeedback_binarized | HuggingFaceH4 | 2023-10-24 | 2024-10-16 | [
"en"
] | mit | [
"text-generation"
] | [
"task_categories:text-generation",
"language:en",
"license:mit",
"size_categories:100K<n<1M",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"arxiv:2310.01377",
"region:us"
] | 100K<n<1M | 16,910 | null | 187,405 | 649,980,296 | [
"2310.01377"
] |
# Dataset Card for UltraFeedback Binarized
## Dataset Description
This is a pre-processed version of the [UltraFeedback dataset](https://huggingface.co/datasets/openbmb/UltraFeedback) and was used to train [Zephyr-7ฮ-ฮฒ](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta), a state of the art chat model at the 7B par... |
dataset | stady4d-anon/StaDy4D | stady4d-anon | 2026-05-02 | 2026-05-07 | [] | cc-by-sa-4.0 | [
"image-to-3d",
"depth-estimation"
] | [
"task_categories:image-to-3d",
"task_categories:depth-estimation",
"license:cc-by-sa-4.0",
"size_categories:n<1K",
"modality:tabular",
"modality:text",
"modality:video",
"region:us",
"4d-reconstruction",
"3d-reconstruction",
"multi-view",
"dynamic-scenes",
"depth",
"camera-poses",
"carla... | n<1K | 18,687 | null | 864 | 1,014,356,774,661 | [] |
# StaDy4D: Static-Dynamic 4D Multi-View Scene Dataset
**StaDy4D** is the first large-scale paired staticโdynamic 4D dataset, comprising **9,000 paired sequences** and **โ1.9M frames** spanning diverse urban environments, camera configurations, camera types, and weather conditions. Each scene is captured with **paired... |
dataset | opendatalab/AICC | opendatalab | 2025-10-15 | 2025-12-25 | [
"multilingual"
] | cc-by-4.0 | [
"text-generation"
] | [
"task_categories:text-generation",
"language:multilingual",
"license:cc-by-4.0",
"size_categories:1B<n<10B",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"arxiv:2511.16397",
"region:us",
"common-crawl",
"html-parsing",
"m... | 1B<n<10B | 16,930 | null | 4,823,698,158 | 11,446,855,368,693 | [
"2511.16397"
] | ๐ง ๐ง **Our New-Gen Html Parser [MinerU-HTML](https://github.com/opendatalab/MinerU-HTML)** Now Realease!
# AICC: AI-ready Common Crawl Dataset
[Paper](https://huggingface.co/papers/2511.16397) | [Project page](https://opendatalab.com/ai-ready/AICC)
<img src="./images/AICC_christmas_LOGO.png" width="600" />
## New... |
dataset | CSU-JPG/TextAtlas5M | CSU-JPG | 2025-02-11 | 2025-10-14 | [
"en"
] | mit | [
"text-to-image"
] | [
"task_categories:text-to-image",
"language:en",
"license:mit",
"size_categories:1M<n<10M",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2502.07870",
"region:us"
] | 1M<n<10M | 16,873 | null | 5,398,826 | 1,202,923,381,122 | [
"2502.07870"
] |
# TextAtlas5M
This dataset is a training set for [TextAtlas](https://textatlas5m.github.io/).
Paper: https://huggingface.co/papers/2502.07870
**(All the data in this repo is uploaded :>)**
# Dataset subsets
Subsets in this dataset are CleanTextSynth, PPT2Details, PPT2Structured,LongWordsSubset-A,LongWordsSubset-M,... |
dataset | HuggingFaceTB/smoltalk | HuggingFaceTB | 2024-11-17 | 2025-02-10 | [
"en"
] | null | [] | [
"language:en",
"size_categories:1M<n<10M",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2502.02737",
"region:us",
"synthetic"
] | 1M<n<10M | 16,821 | null | 2,197,730 | 4,152,709,891 | [
"2502.02737"
] |
# SmolTalk
## Dataset description
This is a synthetic dataset designed for supervised finetuning (SFT) of LLMs. It was used to build [SmolLM2-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-1... |
dataset | fancyzhx/amazon_polarity | fancyzhx | 2022-03-02 | 2024-01-09 | [
"en"
] | apache-2.0 | [
"text-classification"
] | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"source_datasets:original",
"language:en",
"license:apache-2.0",
"size_categories:1M<n<10M",
"format:parquet",
"modali... | 1M<n<10M | 16,649 | [
"monolingual"
] | 4,000,000 | 1,145,438,483 | [
"1509.01626"
] |
# Dataset Card for Amazon Review Polarity
## 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](#dat... |
dataset | ykunboy/MMBrainMRI-4K | ykunboy | 2026-03-12 | 2026-05-01 | [] | null | [] | [
"size_categories:10K<n<100K",
"modality:image",
"modality:text",
"library:datasets",
"library:mlcroissant",
"region:us"
] | 10K<n<100K | 17,295 | null | 21,280 | 81,007,447,319 | [] | |
dataset | microsoft/Updesh_beta | microsoft | 2025-06-24 | 2026-01-25 | [
"as",
"bn",
"en",
"gu",
"hi",
"kn",
"ml",
"mr",
"ne",
"or",
"pa",
"ta",
"te",
"ur"
] | other | [
"question-answering"
] | [
"task_categories:question-answering",
"language:as",
"language:bn",
"language:en",
"language:gu",
"language:hi",
"language:kn",
"language:ml",
"language:mr",
"language:ne",
"language:or",
"language:pa",
"language:ta",
"language:te",
"language:ur",
"license:other",
"size_categories:1M... | 1M<n<10M | 16,765 | null | 8,956,597 | 19,255,337,885 | [
"2509.21294"
] |
# ๐ข Updesh: Synthetic Multilingual Instruction Tuning Dataset for 13 Indic Languages
   [![HuggingFace](https:... |
dataset | nvidia/Nemotron-VLM-Dataset-v2 | nvidia | 2025-10-13 | 2025-12-18 | [] | cc-by-4.0 | [
"visual-question-answering",
"image-text-to-text",
"video-text-to-text"
] | [
"task_categories:visual-question-answering",
"task_categories:image-text-to-text",
"task_categories:video-text-to-text",
"license:cc-by-4.0",
"size_categories:1M<n<10M",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"arxiv:2511.0... | 1M<n<10M | 16,734 | null | 4,518,886 | 600,384,728,774 | [
"2511.03929"
] | # Nemotron-VLM-Dataset v2
## Versions
| Date | Commit | Changes |
|-------------|--------------|----------|
| **2025-11-05** | [head](https://huggingface.co/datasets/nvidia/Nemotron-VLM-Dataset-v2/tree/main) | Fix `nights_cot` dataset. Fix/filter broken <think> entries. Update fintabnet instructi... |
dataset | dmitry-bogachev/terminal-bench-2-leaderboard | dmitry-bogachev | 2026-03-07 | 2026-03-07 | [] | apache-2.0 | [] | [
"license:apache-2.0",
"modality:text",
"region:us"
] | null | 18,196 | null | null | 4,038,077,193 | [] |
# Terminal-Bench 2.0 Leaderboard Submissions
This repository accepts leaderboard submissions for [Terminal-Bench 2.0](https://terminal-bench.org).
## How to Submit
1. [Fork this repository](https://huggingface.co/docs/hub/en/repositories-next-steps#duplicating-with-the-git-history-fork)
2. Create a new bran... |
dataset | astralhf/yonder | astralhf | 2026-04-30 | 2026-05-02 | [
"en"
] | cc-by-nc-4.0 | [
"object-detection",
"depth-estimation",
"robotics"
] | [
"task_categories:object-detection",
"task_categories:depth-estimation",
"task_categories:robotics",
"language:en",
"license:cc-by-nc-4.0",
"size_categories:n<1K",
"modality:text",
"region:us",
"robotics",
"drone-navigation",
"vision-language-navigation",
"open-vocabulary-detection",
"embodie... | n<1K | 19,270 | null | 3 | 871,486,272,546 | [] |
# Yonder: A 4.65M-Frame Drone-Perspective Dataset for Indoor Navigation
> **The cross-simulator generalization gap.**
> Yonder is the largest publicly available drone-perspective dataset for indoor
> navigation, plus a closed-loop benchmark designed to expose a failure mode invisible
> to standard offline metrics: pe... |
dataset | speechcolab/gigaspeech | speechcolab | 2022-06-09 | 2026-02-07 | [
"en"
] | apache-2.0 | [
"automatic-speech-recognition",
"text-to-speech",
"text-to-audio"
] | [
"task_categories:automatic-speech-recognition",
"task_categories:text-to-speech",
"task_categories:text-to-audio",
"multilinguality:monolingual",
"language:en",
"license:apache-2.0",
"size_categories:10M<n<100M",
"format:parquet",
"modality:audio",
"modality:text",
"library:datasets",
"library... | 10M<n<100M | 16,852 | [
"monolingual"
] | null | 2,599,383,342,196 | [
"2106.06909"
] |
# Dataset Card for Gigaspeech
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-struct... |
dataset | CatholicCorpus/catholiccorpus-text | CatholicCorpus | 2026-05-06 | 2026-05-06 | [
"la",
"grc",
"en"
] | other | [
"text-generation",
"feature-extraction",
"fill-mask"
] | [
"task_categories:text-generation",
"task_categories:feature-extraction",
"task_categories:fill-mask",
"language:la",
"language:grc",
"language:en",
"license:other",
"size_categories:n<1K",
"format:text",
"modality:text",
"library:datasets",
"library:mlcroissant",
"region:us",
"catholic",
... | n<1K | 17,465 | null | 673 | 5,968,331,546 | [] |
# CatholicCorpus โ Extracted Text
Pre-extracted plain text from the [CatholicCorpus](https://huggingface.co/datasets/CatholicCorpus/catholiccorpus) โ 2,000 years of the Catholic intellectual tradition, ready for NLP, RAG, and digital humanities.
This dataset contains **47,407 plain text files** (5.7 GB, 2.64 billion... |
dataset | KejueAI/arabic-numbers-tts-dataset | KejueAI | 2026-02-22 | 2026-03-05 | [] | null | [] | [
"size_categories:1K<n<10K",
"format:parquet",
"format:optimized-parquet",
"modality:audio",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"region:us"
] | 1K<n<10K | 17,277 | null | 9,520 | 15,216,494,344 | [] | |
dataset | jiyu9437/gaia_validation | jiyu9437 | 2025-07-11 | 2025-07-11 | [] | null | [] | [
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | n<1K | 16,584 | null | 165 | 162,909 | [] | |
dataset | malteos/wikinews | malteos | 2024-03-11 | 2024-04-16 | [] | null | [] | [
"size_categories:100K<n<1M",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | 100K<n<1M | 16,884 | null | 249,401 | 731,218,818 | [] | # Wikinews
The dataset contains news articles from Wikinews in different languages.
Each article is associated with metadata like title, url, and date.
The articles grouped into data splits by the article month, quarter, and year (the date is one mentioned in the article text, changes might have been after, see revisi... |
dataset | CO-IR/terminal-bench-2-leaderboard | CO-IR | 2026-02-14 | 2026-02-14 | [] | apache-2.0 | [] | [
"license:apache-2.0",
"modality:text",
"region:us"
] | null | 18,144 | null | null | 4,734,915,110 | [] |
# Terminal-Bench 2.0 Leaderboard Submissions
This repository accepts leaderboard submissions for [Terminal-Bench 2.0](https://terminal-bench.org).
## How to Submit
1. [Fork this repository](https://huggingface.co/docs/hub/en/repositories-next-steps#duplicating-with-the-git-history-fork)
2. Create a new bran... |
dataset | Fhrozen/stack-prompts | Fhrozen | 2025-11-19 | 2026-03-06 | [
"en"
] | apache-2.0 | [
"text-generation"
] | [
"task_categories:text-generation",
"language:en",
"license:apache-2.0",
"size_categories:10M<n<100M",
"format:parquet",
"format:optimized-parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"arxiv:2502.02737",
"arxiv:2... | 10M<n<100M | 16,618 | null | 62,153,350 | 154,352,129,850 | [
"2502.02737",
"2402.19173"
] |
# The stack-prompts
This dataset is a curated collection of high-quality educational and synthetic data designed for training (small) language models in coding tasks.
The current dataset comprises three `config names`:
- python-edu: comprises the blob_ids from https://huggingface.co/datasets/HuggingFaceTB/smollm-co... |
dataset | Forceless/PPTAgent-parsed_data | Forceless | 2024-10-18 | 2024-10-20 | [] | null | [] | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:image",
"modality:tabular",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | 1K<n<10K | 17,568 | null | 1,364 | 22,226,137,250 | [] | |
dataset | anon-time-icml/TIME-Output | anon-time-icml | 2026-03-31 | 2026-03-31 | [] | null | [] | [
"size_categories:10K<n<100K",
"format:csv",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"region:us"
] | 10K<n<100K | 16,756 | null | 10,926 | 1,738,954,615 | [] | |
dataset | HuggingFaceH4/orca_dpo_pairs | HuggingFaceH4 | 2023-12-28 | 2024-04-14 | [
"en"
] | mit | [
"conversational",
"text-classification",
"token-classification",
"table-question-answering",
"question-answering",
"zero-shot-classification",
"summarization",
"feature-extraction",
"text-generation",
"text2text-generation"
] | [
"task_categories:text-classification",
"task_categories:token-classification",
"task_categories:table-question-answering",
"task_categories:question-answering",
"task_categories:zero-shot-classification",
"task_categories:summarization",
"task_categories:feature-extraction",
"task_categories:text-gene... | 10K<n<100K | 16,466 | null | 12,859 | 30,780,415 | [
"2306.02707"
] |
# Dataset Card for Orca DPO Pair
## Dataset Description
This is a pre-processed version of the [OpenOrca dataset](https://huggingface.co/datasets/Open-Orca/OpenOrca).
The original OpenOrca dataset is a collection of augmented FLAN data that aligns, as best as possible, with the distributions outlined in the [Orca p... |
dataset | sailor2/sailor2-pretrain-data-stage1 | sailor2 | 2024-10-30 | 2024-12-04 | [] | odc-by | [] | [
"license:odc-by",
"size_categories:100M<n<1B",
"format:json",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"region:us"
] | 100M<n<1B | 16,417 | null | 1,945,467 | 1,934,403,339,759 | [] |
The pre-training dataset (stage1) for the Sailor2 models, including [1B](https://huggingface.co/sail/Sailor2-1B), [8B](https://huggingface.co/sail/Sailor2-8B) and [20B](https://huggingface.co/sail/Sailor2-20B). |
dataset | annoymous-1/CC-Bench | annoymous-1 | 2026-05-03 | 2026-05-03 | [] | other | [
"visual-question-answering",
"image-classification"
] | [
"task_categories:visual-question-answering",
"task_categories:image-classification",
"license:other",
"size_categories:1K<n<10K",
"format:json",
"modality:image",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"region:us",
"medical",
"indust... | 1K<n<10K | 17,441 | null | 4,282 | 9,053,280,356 | [] |
# CC-Bench: A Cognitive Conflict Benchmark for MLLMs in Safety-Critical Visual Inspection
CC-Bench is a joint medical-industrial benchmark for evaluating whether multimodal large language models (MLLMs) remain visually grounded when plausible textual context conflicts with image evidence. The benchmark reorganizes pu... |
dataset | mutakabbirCarleton/NOAH-mini | mutakabbirCarleton | 2025-05-12 | 2025-05-23 | [] | mit | [
"image-to-image"
] | [
"task_categories:image-to-image",
"license:mit",
"size_categories:n<1K",
"format:csv",
"modality:tabular",
"modality:text",
"modality:geospatial",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us",
"art",
"earth",
"remote-sensing",
"satellites",... | n<1K | 16,802 | null | 93 | 51,560,011 | [] |
# MOAH mini
The dataset prest here is a very samll sample of NOAH dataset.
In the original dataset each satellite image is ~650MB with 234,089 images present in 11 bands.
It is not feasible to upload the complete dataset.
A sample of the dataset across diffrent modalities can be seen in the figure below:
![dataset-... |
dataset | yifishbossman/financial-analyst-data-full | yifishbossman | 2026-05-24 | 2026-05-24 | [
"zh"
] | apache-2.0 | [
"time-series-forecasting",
"tabular-classification"
] | [
"task_categories:time-series-forecasting",
"task_categories:tabular-classification",
"language:zh",
"license:apache-2.0",
"size_categories:1K<n<10K",
"modality:text",
"region:us",
"finance",
"a-share",
"chinese-stocks",
"qlib",
"quantitative-trading"
] | 1K<n<10K | 18,043 | null | null | 7,341,785,471 | [] |
# financial-analyst-data-full
A-share historical price + valuation data **packaged for [financial-analyst](https://github.com/jesson-hh/financial-analyst)** โ
the 14-agent single-stock deep-dive research workstation.
**Published**: 2026-05-24
**Preset**: `full` โ ๅ
จ A ่กๅฎๆดๅ
(ๅซๅๅฒ้ๅธ่ก). ้ๅ็ ็ฉถๅ / ้ๅบฆ็จๆท. lite ๅ
จ + TDX ... |
dataset | bertram-gilfoyle/CC-MAIN-2023-06-raw | bertram-gilfoyle | 2024-02-17 | 2024-02-17 | [] | null | [] | [
"size_categories:10M<n<100M",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | 10M<n<100M | 16,317 | null | 24,061,011 | 127,792,121,237 | [] | |
dataset | gmongaras/Imagenet21K | gmongaras | 2025-01-07 | 2025-02-03 | [] | null | [] | [
"size_categories:10M<n<100M",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"region:us"
] | 10M<n<100M | 16,505 | null | 13,153,480 | 3,876,745,907,367 | [] |
NOTE: I have recaptioned all images [here](https://huggingface.co/datasets/gmongaras/Imagenet21K_Recaption)
This dataset is the entire 21K ImageNet dataset with about 13 million examples and about 19 thousand classes as strings
(for some reason it only had ~19K classes instead of 21K).
The images are in PNG format.... |
dataset | lauspectrum/gaia-validation-sampled_50 | lauspectrum | 2025-03-31 | 2025-03-31 | [] | null | [] | [
"size_categories:n<1K",
"format:parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | n<1K | 16,239 | null | 50 | 57,759 | [] | |
dataset | DCAgent2/gaia_127_Kimi_K2_5_20260430_052932-traces | DCAgent2 | 2026-05-01 | 2026-05-01 | [] | null | [] | [
"size_categories:n<1K",
"format:parquet",
"format:optimized-parquet",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"region:us"
] | n<1K | 16,244 | null | 379 | 62,663,474 | [] | |
dataset | ucla-contextual/contextual_test | ucla-contextual | 2024-01-22 | 2024-03-20 | [] | null | [] | [
"size_categories:n<1K",
"format:csv",
"modality:image",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"arxiv:2401.13311",
"region:us"
] | n<1K | 16,216 | null | 506 | 88,116 | [
"2401.13311"
] |
---
license: mit
---
Check out the [paper](https://arxiv.org/abs/2401.13311). |
dataset | facebook/anli | facebook | 2022-03-02 | 2023-12-21 | [
"en"
] | cc-by-nc-4.0 | [
"text-classification"
] | [
"task_categories:text-classification",
"task_ids:natural-language-inference",
"task_ids:multi-input-text-classification",
"annotations_creators:crowdsourced",
"annotations_creators:machine-generated",
"language_creators:found",
"multilinguality:monolingual",
"source_datasets:original",
"source_datas... | 100K<n<1M | 16,355 | [
"monolingual"
] | 169,265 | 26,295,904 | [
"1910.14599"
] |
# Dataset Card for "anli"
## 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 | trl-internal-testing/zen-image | trl-internal-testing | 2025-07-16 | 2026-02-24 | [] | null | [] | [
"size_categories:n<1K",
"format:parquet",
"format:optimized-parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"region:us"
] | n<1K | 16,324 | null | 247 | 1,815,920 | [] | |
dataset | google/deepsearchqa | google | 2025-12-17 | 2025-12-17 | [
"en"
] | apache-2.0 | [
"question-answering"
] | [
"task_categories:question-answering",
"language:en",
"license:apache-2.0",
"size_categories:n<1K",
"format:csv",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us",
"factuality",
"search",
"retrieval",
"deep research",
"comprehen... | n<1K | 16,253 | null | 900 | 361,597 | [] | # DeepSearchQA
#### A 900-prompt factuality benchmark from Google DeepMind, designed to evaluate agents on difficult multi-step information-seeking tasks across 17 different fields.
โถ [Google DeepMind Release Blog Post](https://blog.google/technology/developers/deep-research-agent-gemini-api/)\
โถ [DeepSearchQA Leaderb... |
dataset | lmms-lab/ai2d | lmms-lab | 2024-03-26 | 2024-03-26 | [] | null | [] | [
"size_categories:1K<n<10K",
"format:parquet",
"modality:image",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:1603.07396",
"region:us"
] | 1K<n<10K | 16,268 | null | 3,088 | 139,469,431 | [
"1603.07396"
] |
@misc{kembhavi2016diagram,
title={A Diagram Is Worth A Dozen Images},
author={Aniruddha Kembhavi and Mike Salvato and Eric Kolve and Minjoon Seo and Hannaneh Hajishirzi and Ali Farhadi},
year={2016},
eprint={1603.07396},
archivePrefix={arXiv},
primaryClass={cs.CV}
} |
dataset | Pthahnix/MeshLex-Data-Source | Pthahnix | 2026-04-09 | 2026-04-10 | [] | other | [
"text-to-3d",
"image-to-3d"
] | [
"task_categories:text-to-3d",
"task_categories:image-to-3d",
"license:other",
"size_categories:100K<n<1M",
"format:json",
"modality:3d",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"arxiv:1512.03012",
"region:us",
"3d",
"mesh",
"glb",... | 100K<n<1M | 17,590 | null | 106,635 | 224,371,696,822 | [
"1512.03012"
] |
# MeshLex-Data-Source
A large-scale collection of **158,588 geometry-only GLB meshes** (281 GB) from four major 3D datasets, unified under a single sharded directory structure. Built as the source data layer for the [MeshLex](https://github.com/Pthahnix/MeshLex-Research) research project, but broadly useful for any 3... |
dataset | hendrydong/reinforce-ada-raw-eval | hendrydong | 2026-03-17 | 2026-03-18 | [] | null | [] | [
"modality:text",
"region:us"
] | null | 16,382 | null | null | 48,627,824,626 | [] | # Reinforce-Ada Raw Eval
Raw evaluation artifacts organized by experiment / dataset / step.
Included files when present:
- `merged_data.jsonl`
- `pass_at_k.json`
- `record.txt`
Experiments: grpo_n8, grpo_n16, grpo_n32, reinforce_ada_n8, reinforce_ada_n8_normstdtrue
Datasets: math500, minerva_math, olympiadbench, ai... |
dataset | EarthSpeciesProject/NatureLM-audio-training | EarthSpeciesProject | 2025-02-28 | 2025-06-03 | [
"en"
] | other | [
"audio-classification"
] | [
"task_categories:audio-classification",
"language:en",
"license:other",
"size_categories:10M<n<100M",
"format:parquet",
"modality:audio",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2411.07186",
"region:us",
"biology",
"bioacoustic... | 10M<n<100M | 16,564 | null | 26,440,512 | 17,623,649,813,465 | [
"2411.07186"
] |
# Dataset card for NatureLM-audio-training
## Overview
NatureLM-audio-training is a large and diverse **audio-language dataset** designed for training bioacoustic models that can generate a natural language answer to a natural language query on a reference bioacoustic audio recording.
For example, for an in-the-w... |
dataset | JianhuiWei/UniVBench | JianhuiWei | 2026-03-23 | 2026-05-27 | [
"en",
"zh"
] | other | [
"text-to-video",
"image-to-video",
"image-text-to-video",
"video-to-video",
"video-text-to-text",
"any-to-any",
"other"
] | [
"task_categories:text-to-video",
"task_categories:image-to-video",
"task_categories:image-text-to-video",
"task_categories:video-to-video",
"task_categories:video-text-to-text",
"task_categories:any-to-any",
"task_categories:other",
"language:en",
"language:zh",
"license:other",
"size_categories... | 1K<n<10K | 16,464 | null | 1,036 | 17,702,338,232 | [
"2602.21835"
] |
# UniVBench
UniVBench is a unified benchmark for video generation and video editing tasks, covering text-guided video editing, reference-guided video generation, captioning, and multimodal evaluation scenarios.
## Dataset Download
To download the whole UniVBench dataset, run the following command in your terminal:... |
dataset | kohsei/MultiBanana-Benchmark | kohsei | 2025-11-27 | 2026-03-27 | [
"en"
] | cc-by-nc-4.0 | [
"text-to-image"
] | [
"task_categories:text-to-image",
"language:en",
"license:cc-by-nc-4.0",
"size_categories:1K<n<10K",
"format:imagefolder",
"modality:image",
"modality:text",
"library:datasets",
"library:mlcroissant",
"arxiv:2511.22989",
"region:us"
] | 1K<n<10K | 16,379 | null | 4,700 | 8,888,376,788 | [
"2511.22989"
] |
<h1 align="center">๐ MultiBanana: A Challenging Benchmark for Multi-Reference Text-to-Image Generation ๐</h1>
<p align="center">
<b>CVPR 2026 (Main)</b>
</p>
This repository provides the datasets for
**โMultiBanana: A Challenging Benchmark for Multi-Reference Text-to-Image Generationโ by Yuta Oshima, Daiki Mi... |
dataset | hf-internal-testing/raw_jsonl | hf-internal-testing | 2023-08-24 | 2021-07-06 | [] | null | [] | [
"size_categories:10K<n<100K",
"format:json",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"region:us"
] | 10K<n<100K | 16,039 | null | 11,000 | 3,941,370 | [] | |
dataset | anivcsh/supreme-court-data | anivcsh | 2026-04-18 | 2026-04-23 | [] | cc-by-4.0 | [] | [
"license:cc-by-4.0",
"size_categories:10K<n<100K",
"modality:document",
"modality:text",
"library:datasets",
"library:mlcroissant",
"region:us"
] | 10K<n<100K | 17,041 | null | 43,425 | 4,257,906,068 | [] | |
dataset | HuggingFaceTB/cosmopedia | HuggingFaceTB | 2024-02-18 | 2024-08-12 | [
"en"
] | apache-2.0 | [] | [
"language:en",
"license:apache-2.0",
"size_categories:10M<n<100M",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2309.05463",
"arxiv:2306.11644",
"region:us",
"synthetic"
] | 10M<n<100M | 16,015 | null | 31,064,744 | 92,200,797,209 | [
"2309.05463",
"2306.11644"
] |
# Cosmopedia v0.1
<center>
<img src="https://cdn-uploads.huggingface.co/production/uploads/61c141342aac764ce1654e43/8a9ZTW8sC4utjEPIrZegN.png" alt="Cosmopedia v0.1" width="600" height="300">
<p><em>Image generated by DALL-E, the <a href="https://huggingface.co/datasets/HuggingFaceTB/miscellaneous/blob/main/cos... |
dataset | jiang-cc/MMAD | jiang-cc | 2024-10-17 | 2025-08-06 | [] | cc-by-nc-sa-4.0 | [
"question-answering"
] | [
"task_categories:question-answering",
"license:cc-by-nc-sa-4.0",
"size_categories:10K<n<100K",
"format:csv",
"modality:image",
"modality:text",
"library:datasets",
"library:pandas",
"library:mlcroissant",
"library:polars",
"arxiv:2410.09453",
"region:us",
"Anomaly Detection",
"MLLM"
] | 10K<n<100K | 16,120 | null | 39,672 | 28,365,325,832 | [
"2410.09453"
] |
# MMAD: The First-Ever Comprehensive Benchmark for Multimodal Large Language Models in Industrial Anomaly Detection
[](https://arxiv.org/abs/2410.09453)
[](https://github.com/jam-cc/MMAD)
## ๐ก This dataset... |
dataset | trentmkelly/scored_co_2025 | trentmkelly | 2025-10-22 | 2026-05-12 | [
"en"
] | cc-by-sa-4.0 | [
"text-generation",
"text-classification"
] | [
"task_categories:text-generation",
"task_categories:text-classification",
"language:en",
"license:cc-by-sa-4.0",
"size_categories:10M<n<100M",
"format:parquet",
"modality:tabular",
"modality:text",
"library:datasets",
"library:dask",
"library:polars",
"library:mlcroissant",
"region:us",
"r... | 10M<n<100M | 16,485 | null | 73,045,361 | 25,999,783,794 | [] |
# Scored.co 2025 scrape
This dataset is a full scrape of public content from [Scored.co](https://scored.co/), a right-wing Reddit-style social media site. It contains **73,045,361 rows** of posts and comments, stored as parquet.
The dataset is intended for research into online communities, political discussion, soci... |
dataset | nips26/VoxSafeBench | nips26 | 2026-05-01 | 2026-05-01 | [
"en",
"zh"
] | apache-2.0 | [] | [
"language:en",
"language:zh",
"license:apache-2.0",
"size_categories:1K<n<10K",
"format:json",
"modality:audio",
"modality:text",
"library:datasets",
"library:pandas",
"library:polars",
"library:mlcroissant",
"region:us",
"audio",
"safety",
"fairness",
"privacy"
] | 1K<n<10K | 17,090 | null | 3,912 | 25,386,953,071 | [] | # VoxSafeBench
This dataset is uploaded as raw files (JSONL + audio), not parquet.
## Subset: Safety-tier1
### Split: No_jailbreak (8708 samples)
Columns: system_prompt, clean_audio_file_name, diverse_audio_file_name, transcript, super_category, task_type, language, query
### Split: Singleturn_jailbreak (2516 sampl... |
dataset | Open-Orca/FLAN | Open-Orca | 2023-07-21 | 2023-08-02 | [
"en"
] | cc-by-4.0 | [] | [
"language:en",
"license:cc-by-4.0",
"size_categories:100M<n<1B",
"format:parquet",
"modality:text",
"library:datasets",
"library:dask",
"library:mlcroissant",
"library:polars",
"arxiv:2301.13688",
"arxiv:2109.01652",
"arxiv:2110.08207",
"arxiv:2204.07705",
"region:us"
] | 100M<n<1B | 16,161 | null | 377,759,274 | 411,908,012,824 | [
"2301.13688",
"2109.01652",
"2110.08207",
"2204.07705"
] |
<p><h1>๐ฎ The WHOLE FLAN Collection! ๐ฎ</h1></p>
# Overview
This repository includes the full dataset from the [FLAN Collection](https://ai.googleblog.com/2023/02/the-flan-collection-advancing-open.html), tot... |
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