datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
mbpp
Dataset Card for Mostly Basic Python Problems (mbpp)
Dataset Summary
The benchmark consists of around 1,000 crowd-sourced Python programming problems, designed to be solvable by entry level programmers, covering programming fundamentals, standard library functionality, and so on. Each problem consists of a task description, code solution and 3 automated test cases. As described in the paper, a subset of the data has been hand-verified by us.
Released here as part of… See the full description on the dataset page: https://huggingface.co/datasets/google-research-datasets/mbpp.IFEval
Dataset Card for IFEval
Dataset Summary
This dataset contains the prompts used in the Instruction-Following Eval (IFEval) benchmark for large language models. It contains around 500 "verifiable instructions" such as "write in more than 400 words" and "mention the keyword of AI at least 3 times" which can be verified by heuristics. To load the dataset, run:
from datasets import load_dataset
ifeval = load_dataset("google/IFEval")
Supported Tasks and… See the full description on the dataset page: https://huggingface.co/datasets/google/IFEval.seedance-2-prompts-datasets
🎞️ Seedance-2-prompts-datasets
🎞️ The ultimate Seedance-2 video prompt dataset (50GB+). 8100+ video generation prompts with full metadata and preview frames. Truly open source: No login, no ads, no redirection. Just pure data for AI video creators.
This project is a massive collection of prompts used for Bytedance's Seedance 2.0 and the resulting generated videos. The entire dataset exceeds 50GB and contains 8100+ videos, all structured into a comprehensive dataset.
Due… See the full description on the dataset page: https://huggingface.co/datasets/GokuScraper/seedance-2-prompts-datasets.Berkeley-Function-Calling-Leaderboard
Berkeley Function Calling Leaderboard
The Berkeley function calling leaderboard is a live leaderboard to evaluate the ability of different LLMs to call functions (also referred to as tools).
We built this dataset from our learnings to be representative of most users' function calling use-cases, for example, in agents, as a part of enterprise workflows, etc.
To this end, our evaluation dataset spans diverse categories, and across multiple languages.
Checkout the Leaderboard at… See the full description on the dataset page: https://huggingface.co/datasets/gorilla-llm/Berkeley-Function-Calling-Leaderboard.paws
Dataset Card for PAWS: Paraphrase Adversaries from Word Scrambling
Dataset Summary
PAWS: Paraphrase Adversaries from Word Scrambling
This dataset contains 108,463 human-labeled and 656k noisily labeled pairs that feature the importance of modeling structure, context, and word order information for the problem of paraphrase identification. The dataset has two subsets, one based on Wikipedia and the other one based on the Quora Question Pairs (QQP) dataset.
For further… See the full description on the dataset page: https://huggingface.co/datasets/google-research-datasets/paws.ReActor
ReActor Assets
The Fast and Simple Face Swap Extension
ComfyUI-ReActor (ex. comfyui-reactor-node)
sd-webui-reactor
Models
file
source
license
buffalo_l.zip
DeepInsight
codeformer-v0.1.0.pth
sczhou
GFPGANv1.3.pth
TencentARC
GFPGANv1.4.pth
TencentARC
GPEN-BFR-512.onnx
harisreedhar
RestoreFormer_PP.onnx
netrunner.exe
inswapper_128.onnx
DeepInsight
inswapper_128_fp16.onnx
Hillobar
fleurs
FLEURS
Fleurs is the speech version of the FLoRes machine translation benchmark.
We use 2009 n-way parallel sentences from the FLoRes dev and devtest publicly available sets, in 102 languages.
Training sets have around 10 hours of supervision. Speakers of the train sets are different than speakers from the dev/test sets. Multilingual fine-tuning is
used and ”unit error rate” (characters, signs) of all languages is averaged. Languages and results are also grouped into seven… See the full description on the dataset page: https://huggingface.co/datasets/google/fleurs.gpt-image-2-prompts-datasets
🖼️ GPT Image 2 Prompt Dataset
🖼️ The ultimate GPT Image 2 prompt dataset (5GB+). 15,000+ image generation prompts with full metadata and preview images. Truly open source: No login, no ads, no redirection. Just pure data for AI image creators.
This project is a massive collection of prompts used for OpenAI's GPT Image 2 model and the resulting generated images. The entire dataset exceeds 5GB and contains 15,000+ images, all structured into a comprehensive dataset.
Due to… See the full description on the dataset page: https://huggingface.co/datasets/Goku-OpenLab/gpt-image-2-prompts-datasets.boolq
Dataset Card for Boolq
Dataset Summary
BoolQ is a question answering dataset for yes/no questions containing 15942 examples. These questions are naturally
occurring ---they are generated in unprompted and unconstrained settings.
Each example is a triplet of (question, passage, answer), with the title of the page as optional additional context.
The text-pair classification setup is similar to existing natural language inference tasks.
Supported Tasks and… See the full description on the dataset page: https://huggingface.co/datasets/google/boolq.svq
Simple Voice Questions
Simple Voice Questions (SVQ) is a set of short audio questions recorded in 26 locales across 17 languages under multiple audio conditions. It serves as a core evaluation componenet for Massive Sound Embedding Benchmark (MSEB).
Technical Specifications
Feature
Details
Locales
26
Languages
17
Total Speakers
~700 (Capped at 250 recordings per speaker)
Audio Conditions
Clean, Background Speech, Media, Traffic Noise
Gender… See the full description on the dataset page: https://huggingface.co/datasets/google/svq.goldsrc-models-datasetai4g-flood-dataset
Flood Detection Dataset
Introduction
This dataset accompanies the paper Mapping global floods with 10 years of satellite radar data (Nature Communications, 2025) and contains global flood detections derived from Sentinel-1 Synthetic Aperture Radar (SAR) imagery using a deep learning change detection model. The dataset spans October 2014 – September 2024, offering a longitudinal view of flood-prone areas worldwide.
Key features:
Cloud-penetrating SAR data for consistent… See the full description on the dataset page: https://huggingface.co/datasets/ai-for-good-lab/ai4g-flood-dataset.xtreme
Dataset Card for "xtreme"
Dataset Summary
The Cross-lingual Natural Language Inference (XNLI) corpus is a crowd-sourced collection of 5,000 test and
2,500 dev pairs for the MultiNLI corpus. The pairs are annotated with textual entailment and translated into
14 languages: French, Spanish, German, Greek, Bulgarian, Russian, Turkish, Arabic, Vietnamese, Thai, Chinese,
Hindi, Swahili and Urdu. This results in 112.5k annotated pairs. Each premise can be associated with the… See the full description on the dataset page: https://huggingface.co/datasets/google/xtreme.GoPro-Raw-Videos
Raw GoPro Videos for Four Robotic Manipulation Tasks
[Project Page]
[Paper]
[Code]
[Models]
[Processed Dataset]
This repository contains raw GoPro videos of robotic manipulation tasks collected in-the-wild using UMI, as described in the paper "Data Scaling Laws in Imitation Learning for Robotic Manipulation". The dataset covers four tasks:
Pour Water
Arrange Mouse
Fold Towel
Unplug Charger
Dataset Folders:
arrange_mouse and pour_water: Each folder contains data… See the full description on the dataset page: https://huggingface.co/datasets/Fanqi-Lin/GoPro-Raw-Videos.nq_open
Dataset Card for nq_open
Dataset Summary
The NQ-Open task, introduced by Lee et.al. 2019,
is an open domain question answering benchmark that is derived from Natural Questions.
The goal is to predict an English answer string for an input English question.
All questions can be answered using the contents of English Wikipedia.
Supported Tasks and Leaderboards
Open Domain Question-Answering,
EfficientQA Leaderboard:… See the full description on the dataset page: https://huggingface.co/datasets/google-research-datasets/nq_open.nano-banana-pro-prompts-datasets
🖼️ Nano Banana Pro Prompt Dataset
🖼️ The ultimate Nano Banana Pro prompt dataset (6GB+). 26,000+ image generation prompts with full metadata and preview images. Truly open source: No login, no ads, no redirection. Just pure data for AI image creators.
This project is a massive collection of prompts used for Nano Banana Pro AI image model and the resulting generated images. The entire dataset exceeds 6GB and contains 26,000+ images, all structured into a comprehensive… See the full description on the dataset page: https://huggingface.co/datasets/Goku-OpenLab/nano-banana-pro-prompts-datasets.deepsearchqa
DeepSearchQA
A 900-prompt factuality benchmark from Google DeepMind, designed to evaluate agents on difficult multi-step information-seeking tasks across 17 different fields.
▶ Google DeepMind Release Blog Post▶ DeepSearchQA Leaderboard on Kaggle▶ Technical Report▶ Evaluation Starter Code
Benchmark
DeepSearchQA is a 900-prompt benchmark for evaluating agents on difficult multi-step information-seeking tasks across 17 different fields. Unlike traditional… See the full description on the dataset page: https://huggingface.co/datasets/google/deepsearchqa.BLOCK-0000004natural_questions
Dataset Card for Natural Questions
Dataset Summary
The NQ corpus contains questions from real users, and it requires QA systems to
read and comprehend an entire Wikipedia article that may or may not contain the
answer to the question. The inclusion of real user questions, and the
requirement that solutions should read an entire page to find the answer, cause
NQ to be a more realistic and challenging task than prior QA datasets.
Supported Tasks and Leaderboards… See the full description on the dataset page: https://huggingface.co/datasets/google-research-datasets/natural_questions.go_emotions
Dataset Card for GoEmotions
Dataset Summary
The GoEmotions dataset contains 58k carefully curated Reddit comments labeled for 27 emotion categories or Neutral.
The raw data is included as well as the smaller, simplified version of the dataset with predefined train/val/test
splits.
Supported Tasks and Leaderboards
This dataset is intended for multi-class, multi-label emotion classification.
Languages
The data is in English.
Dataset Structure… See the full description on the dataset page: https://huggingface.co/datasets/google-research-datasets/go_emotions.wmt24pp
WMT24++
This repository contains the human translation and post-edit data for the 55 en->xx language pairs released in
the publication
WMT24++: Expanding the Language Coverage of WMT24 to 55 Languages & Dialects.
If you are interested in the MT/LLM system outputs and automatic metric scores, please see MTME.
If you are interested in the images of the source URLs for each document, please see here.
Schema
Each language pair is stored in its own jsonl file.
Each row… See the full description on the dataset page: https://huggingface.co/datasets/google/wmt24pp.frames-benchmark
FRAMES: Factuality, Retrieval, And reasoning MEasurement Set
FRAMES is a comprehensive evaluation dataset designed to test the capabilities of Retrieval-Augmented Generation (RAG) systems across factuality, retrieval accuracy, and reasoning.
Our paper with details and experiments is available on arXiv: https://arxiv.org/abs/2409.12941.
Dataset Overview
824 challenging multi-hop questions requiring information from 2-15 Wikipedia articles
Questions span diverse topics… See the full description on the dataset page: https://huggingface.co/datasets/google/frames-benchmark.warp-speed
WarpSpeed Research Dataset
Dataset Summary
The WarpSpeed Research Dataset is a comprehensive collection of scientific research papers, experimental data, and theoretical materials focused on advanced propulsion concepts and physics principles inspired by Star Trek technologies. This dataset combines real-world physics research with theoretical frameworks to explore the possibilities of faster-than-light travel and advanced energy systems.
Data Collection and… See the full description on the dataset page: https://huggingface.co/datasets/GotThatData/warp-speed.GOKU-2M
Goku: A Million-Scale Universal Dataset and Benchmark for Instruction-Based Video Editing
GOKU-2M is a large-scale, unified instruction-based video-editing dataset covering 10 editing tasks. Each sample provides a source video, an edited target video, and one or more natural-language instructions describing the edit.
📦 Repositories
⚠️ Because a single Hugging Face account has a free storage quota of about 8.7 TB, the dataset is split across two… See the full description on the dataset page: https://huggingface.co/datasets/bigfacing/GOKU-2M.conceptual_captions
Dataset Card for Conceptual Captions
Dataset Summary
Conceptual Captions is a dataset consisting of ~3.3M images annotated with captions. In contrast with the curated style of other image caption annotations, Conceptual Caption images and their raw descriptions are harvested from the web, and therefore represent a wider variety of styles. More precisely, the raw descriptions are harvested from the Alt-text HTML attribute associated with web images. To arrive at the… See the full description on the dataset page: https://huggingface.co/datasets/google-research-datasets/conceptual_captions.GOCE-satellite-telemtryUtilisation of this data is subject to European Space Agency's Earth Observation Terms and Conditions. Read T&C here
This is Dataset Version 3 - Updates may be done following feedback from the machine learning community.
Dataset Description
This dataset contains 327 time series corresponding to the temporal values of 327 telemetry parameters over the life of the real GOCE satellite (from March 2009 to October 2013). It consists both the raw data and Machine-Learning ready-to-use… See the full description on the dataset page: https://huggingface.co/datasets/patrickfleith/GOCE-satellite-telemtry.IndustryCorpus2_current_affairs_government_administration
IndustryCorpus2: Politics & Administration
This repository contains the IndustryCorpus2: Politics & Administration domain subset of BAAI/IndustryCorpus2.
Refer to the parent dataset card for data construction, intended use, limitations,
and licensing details.
Citation
If you use this dataset in your work, please cite IndustryCorpus2:
@misc{shi2024industrycorpus2,
title = {IndustryCorpus2},
author = {Xiaofeng Shi and Lulu Zhao and Hua Zhou and Donglin… See the full description on the dataset page: https://huggingface.co/datasets/BAAI/IndustryCorpus2_current_affairs_government_administration.libero_gen_goal_chain_hdf5fish-food
Goldfish Datasets
These are the training datasets for the Goldfish models, as described in our paper, Goldfish: Monolingual Language Models for 350 Languages (Chang et al., 2026).
Citation
Along with citing the Goldfish paper, if using this dataset, we encourage researchers to cite the individual datasets listed in our paper.
@inproceedings{chang-etal-2026-goldfish,
title={Goldfish: Monolingual Language Models for 350 Languages},
author={Chang, Tyler A. and Arnett… See the full description on the dataset page: https://huggingface.co/datasets/goldfish-models/fish-food.wiki40b
Dataset Card for "wiki40b"
Dataset Summary
Clean-up text for 40+ Wikipedia languages editions of pages
correspond to entities. The datasets have train/dev/test splits per language.
The dataset is cleaned up by page filtering to remove disambiguation pages,
redirect pages, deleted pages, and non-entity pages. Each example contains the
wikidata id of the entity, and the full Wikipedia article after page processing
that removes non-content sections and structured objects.… See the full description on the dataset page: https://huggingface.co/datasets/google/wiki40b.