datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
newyorker_caption_contest
Dataset Card for New Yorker Caption Contest Benchmarks
Dataset Summary
See capcon.dev for more!
Data from:
Do Androids Laugh at Electric Sheep? Humor "Understanding" Benchmarks from The New Yorker Caption Contest
@inproceedings{hessel2023androids,
title={Do Androids Laugh at Electric Sheep? {Humor} ``Understanding''
Benchmarks from {The New Yorker Caption Contest}},
author={Hessel, Jack and Marasovi{\'c}, Ana and Hwang, Jena D. and Lee, Lillian
and… See the full description on the dataset page: https://huggingface.co/datasets/jmhessel/newyorker_caption_contest.danbooru-1024-eq-captioned
Danbooru 1024 e/q Captioned Dataset
59,495 high-resolution (1024px) anime-style images from Danbooru's explicit and questionable rated pools. Each image includes comprehensive JSON captions generated via MiniMax-M3 with structured per-character state-of-dress inventories, camera notes, mood palettes, and post-processing detections.
Directory Structure
danbooru-1024-eq-captioned.parquet <- consolidated metadata manifest
originals/ <-… See the full description on the dataset page: https://huggingface.co/datasets/quarterturn/danbooru-1024-eq-captioned.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.Embodied-Captioning
Embodied Image Captioning – Manually Annotated Test Set
Paper: Embodied Image Captioning: Self-supervised Learning Agents for Spatially Coherent Image Descriptions (ICCV 2025)Authors: Tommaso Galliena, Tommaso Apicella, Stefano Rosa, Pietro Morerio, Alessio Del Bue, Lorenzo NataleAffiliations: Italian Institute of Technology (IIT), University of GenoaProject Website: https://hsp-iit.github.io/embodied-captioningCode: https://github.com/hsp-iit/embodied-captioning
📦… See the full description on the dataset page: https://huggingface.co/datasets/TommyBsk/Embodied-Captioning.ramanv-image-captions-realconceptual-captions-12m-webdatasetBLIP3o-Pretrain-Long-Caption
BLIP3o Pretrain Long-Caption Dataset
This collection contains 27 million images, each paired with a long (~120 token) caption generated by Qwen/Qwen2.5-VL-7B-Instruct.
Download
from huggingface_hub import snapshot_download
snapshot_download(
repo_id="BLIP3o/BLIP3o-Pretrain-Long-Caption",
repo_type="dataset"
)
Load Dataset without Extracting
You don’t need to unpack the .tar archives, use WebDataset support in 🤗datasets instead:
from datasets import… See the full description on the dataset page: https://huggingface.co/datasets/BLIP3o/BLIP3o-Pretrain-Long-Caption.laions_got_talent_enhanced_flash_annotations_and_long_captionspokemon-blip-captions
Notice of DMCA Takedown Action
We have received a DMCA takedown notice from The Pokémon Company International, Inc.
In response to this action, we have taken down the dataset.
We appreciate your understanding.
conceptual-captions-12m-webdataset-metadata
Conceptual Captions 12M — Webshart metadata indices
Per-shard webshart metadata indices for
laion/conceptual-captions-12m-webdataset:
1,100 JSON files under data/, one per source tar shard, mirroring the source's shard layout.
Each index records every tar member's byte offset and length (enabling ranged reads without
downloading whole shards), image geometry (width/height for aspect bucketing), and — as of
August 2026 — embedded captions for all 10,994,853 samples, coalesced… See the full description on the dataset page: https://huggingface.co/datasets/webshart/conceptual-captions-12m-webdataset-metadata.BLIP3o-Pretrain-Short-Caption
BLIP3o Pretrain Short-Caption Dataset
This collection contains 5 million images, each paired with a short (~20 token) caption generated by Qwen/Qwen2.5-VL-7B-Instruct.
Download
from huggingface_hub import snapshot_download
snapshot_download(
repo_id="BLIP3o/BLIP3o-Pretrain-Short-Caption",
repo_type="dataset"
)
Load Dataset without Extracting
You don’t need to unpack the .tar archives, use WebDataset support in 🤗datasets instead:
from datasets import… See the full description on the dataset page: https://huggingface.co/datasets/BLIP3o/BLIP3o-Pretrain-Short-Caption.COCO-Caption
Large-scale Multi-modality Models Evaluation Suite
Accelerating the development of large-scale multi-modality models (LMMs) with lmms-eval
🏠 Homepage | 📚 Documentation | 🤗 Huggingface Datasets
This Dataset
This is a formatted version of COCO-Caption-2014-version. It is used in our lmms-eval pipeline to allow for one-click evaluations of large multi-modality models.
@misc{lin2015microsoft,
title={Microsoft COCO: Common Objects in Context}… See the full description on the dataset page: https://huggingface.co/datasets/lmms-lab-encoder/COCO-Caption.coco_captions
Dataset Card for "coco_captions"
More Information needed
youtube_caption_yue
YouTube ASR Caption Dataset (Cantonese)
This dataset was built from YouTube videos with manually provided captions in Cantonese. We used SenseVoice to re-transcribe the audio and filtered segments to build a high-quality collection of audio-caption pairs.
What’s included
Segments where the ASR output is identical to the original caption — likely clean.
Segments where differences are only homophones (同音字) or English words — likely ASR mistakes.
This combination supports… See the full description on the dataset page: https://huggingface.co/datasets/ming030890/youtube_caption_yue.BridgeData2-Subset-Synthetic-Captions
BridgeData2 Subset Synthetic Captions
Dataset Summary
nvidia/BridgeData2-Subset-Synthetic-Captions is a subset of BridgeData V2 packaged with short robot-manipulation video clips and synthetic video captions. It is intended for supervised fine-tuning (SFT), prompt generation, and evaluation workflows involving text-to-video, image-to-video, and video-to-video generation of robot manipulation scenes.
The source data is derived from BridgeData V2, a large-scale… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/BridgeData2-Subset-Synthetic-Captions.COCO-Caption2017
Large-scale Multi-modality Models Evaluation Suite
Accelerating the development of large-scale multi-modality models (LMMs) with lmms-eval
🏠 Homepage | 📚 Documentation | 🤗 Huggingface Datasets
This Dataset
This is a formatted version of COCO-Caption-2017-version. It is used in our lmms-eval pipeline to allow for one-click evaluations of large multi-modality models.
@misc{lin2015microsoft,
title={Microsoft COCO: Common Objects in Context}… See the full description on the dataset page: https://huggingface.co/datasets/lmms-lab-encoder/COCO-Caption2017.conceptual-captions-12m-webdataset-bertsffhq512-captionlaion2b-en-a65_cogvlm2-4bit_captions
Abstract
This dataset contains image captions for the laion2B-en aesthetics>=6.5 image dataset using CogVLM2-4bit with the "laion-pop"-prompt to generate captions which were "likely" used in Stable Diffusion 3 training. From these image captions new synthetic images were generated using stable-diffusion-3-medium (batch-size=8).
The synthetic images are best viewed locally by cloning this repo with:
git lfs install
git clone… See the full description on the dataset page: https://huggingface.co/datasets/GeroldMeisinger/laion2b-en-a65_cogvlm2-4bit_captions.fixtures-captioning\\ni1-captionsi1: A Simple and Fully Open Recipe for Strong Text-to-Image Models
Boya Zeng, Tianze Luo, Shu Pu, Jucheng Shen, Taiming Lu, Gabriel Sarch, Zhuang Liu
Princeton University
[arXiv][code][model][project page]
1. Overview
This dataset contains all captions used in our controlled experiments and the final training of the i1 model. Detailed instructions for downloading the corresponding images and matching the image-caption pairs can be found in our codebase.
2.… See the full description on the dataset page: https://huggingface.co/datasets/zlab-princeton/i1-captions.majestrino-unified-detailed-captions
Majestrino Unified Detailed Captions
Filtered subset of laion/majestrino-data containing all samples with unified_detailed_caption.
Stats
4,658,407 samples
932 tar files (~1.1 GB each)
~1,017 GB total
Format
Each tar contains paired .flac + .json files.
JSON fields:
caption — the unified detailed caption
caption_type — always unified_detailed_caption
transcription — speech transcription (when available, normalized from multiple source keys)
duration — audio… See the full description on the dataset page: https://huggingface.co/datasets/TTS-AGI/majestrino-unified-detailed-captions.laions-got-talent-shuffled-with-long-captionssynthetic-dataset-1m-dalle3-high-quality-captions
Dataset Card for Dalle3 1 Million+ High Quality Captions
Alt name: Human Preference Synthetic Dataset
Example grids for landscapes, cats, creatures, and fantasy are also available.
Description:
This dataset comprises of AI-generated images sourced from various websites and individuals, primarily focusing on Dalle 3 content, along with contributions from other AI systems of sufficient quality like Stable Diffusion and Midjourney (MJ v5 and above). As users typically… See the full description on the dataset page: https://huggingface.co/datasets/ProGamerGov/synthetic-dataset-1m-dalle3-high-quality-captions.captioned-ai-music-snippets
Dataset Overview
A collection of short audio snippets (3–30 seconds) extracted from publicly shared Suno‑generated songs and captioned with Gemini Flash 2.0. Designed specifically to train and evaluate audio captioning models.
Source
Clips are randomly cut from the songs referenced in the nyuuzyou/suno repository.
Captioning
All excerpts have been annotated using Gemini Flash 2.0 for high‑quality, human‑readable audio descriptions.
License
Apache 2.0
naruto-blip-captions
Dataset Card for Naruto BLIP captions
Dataset used to train TBD.
The original images were obtained from narutopedia.com and captioned with the pre-trained BLIP model.
For each row the dataset contains image and text keys. image is a varying size PIL jpeg, and text is the accompanying text caption. Only a train split is provided.
Example stable diffusion outputs
"Bill Gates with a hoodie", "John Oliver with Naruto style", "Hello Kitty with Naruto style", "Lebron… See the full description on the dataset page: https://huggingface.co/datasets/lambda/naruto-blip-captions.captionbert-8192-v2-consensusramanv-image-captions-11ActivityNet_Captions
About
ActivityNet Captions contains 20K long-form videos (180s as average length) from YouTube and 100K captions. Most of the videos contain over 3 annotated events. We follow the existing works to concatenate multiple short temporal descriptions into long sentences and evaluate ‘paragraph-to-video’ retrieval on this benchmark.
We adopt the official split:
Train: 10,009 videos, 10,009 captions (concatenate from 37,421 short captions)
Test (Val1): 4,917 videos, 4,917 captions… See the full description on the dataset page: https://huggingface.co/datasets/friedrichor/ActivityNet_Captions.video_captioning