datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Hy-Embodied-0.5-VLA-Data
Hy-Embodied-0.5-VLA
From Vision-Language-Action Models to a Real-World Robot Learning Stack
Tencent Robotics X × Tencent Hy Team
📖 Abstract
We introduce Hy-Embodied-0.5-VLA (Hy-VLA) — an end-to-end Vision-Language-Action system that spans the full robot learning stack: data collection, model design, pre-training, supervised fine-tuning, RL post-training, and real-world deployment. Built on the Hy-Embodied-0.5 MoT backbone, Hy-VLA integrates a flow-matching… See the full description on the dataset page: https://huggingface.co/datasets/tencent/Hy-Embodied-0.5-VLA-Data.vllm-control-arena
vLLM Main Tasks Dataset
AI coding tasks generated from vLLM git commits
Dataset Description
This dataset contains 6801 coding tasks automatically generated from git commits in the vLLM repository. Each task represents a real-world coding challenge derived from actual development work.
Dataset Structure
The dataset contains the following columns:
commit_hash: The git commit hash
parent_hash: The parent commit hash
commit_title: The original commit… See the full description on the dataset page: https://huggingface.co/datasets/RoganInglis/vllm-control-arena.Recap-DataComp-1B
Dataset Card for Recap-DataComp-1B
Recap-DataComp-1B is a large-scale image-text dataset that has been recaptioned using an advanced LLaVA-1.5-LLaMA3-8B model to enhance the alignment and detail of textual descriptions.
Dataset Details
Dataset Description
Our paper aims to bridge this community effort, leveraging the powerful and open-sourced LLaMA-3, a GPT-4 level LLM.
Our recaptioning pipeline is simple: first, we fine-tune a LLaMA-3-8B powered… See the full description on the dataset page: https://huggingface.co/datasets/UCSC-VLAA/Recap-DataComp-1B.MSR-VTTClone from "friedrichor/MSR-VTT".
MSRVTT contains 10K video clips and 200K captions.
We adopt the standard 1K-A split protocol, which was introduced in JSFusion and has since become the de facto benchmark split in the Text-Video Retrieval field.
Train:
train_7k: 7,010 videos, 140,200 captions
train_9k: 9,000 videos, 180,000 captions
Test:
test_1k: 1,000 videos, 1,000 captions
🌟 Citation
@inproceedings{xu2016msrvtt,
title={Msr-vtt: A large video description dataset… See the full description on the dataset page: https://huggingface.co/datasets/VLM2Vec/MSR-VTT.vlabench_composite_ft_lerobot_videovlabench_primitive_ft_lerobot_video
VLABench Primitive Tasks Dataset - LeRobot v3.0
Dataset Description
This dataset is organized in the LeRobot v3.0 format and is used for integrating VLABench into the LeRobot framework officially.
Compared with the v2.0 version and the RLDS version of the dataset, this release stores visual observations in a video-compressed format rather than as individual image files. This design provides significant advantages in both storage efficiency and data loading performance.… See the full description on the dataset page: https://huggingface.co/datasets/VLABench/vlabench_primitive_ft_lerobot_video.GMAI-VL-5.5M
GMAI-VL-5.5M Dataset
GMAI-VL-5.5M is a comprehensive, large-scale medical General Medical AI Vision-Language (GMAI-VL) dataset built specifically for training multimodal foundation models in the medical domain. It contains an extraordinary scale of high-quality instructions encompassing over 5.5 million multimodal question-answering pairs, carefully constructed based on hundreds of medical classification, segmentation, and detection datasets.
This repository… See the full description on the dataset page: https://huggingface.co/datasets/General-Medical-AI/GMAI-VL-5.5M.vllm-traces-v2MMLongBench-docVista
Dataset Card for "Vista"
"700.000 Vietnamese vision-language samples open-source dataset"
Dataset Overview
This dataset contains over 700,000 Vietnamese vision-language samples, created by Gemini Pro. We employed several prompt engineering techniques: few-shot learning, caption-based prompting and image-based prompting.
For the COCO dataset, we generated data using Llava-style prompts
For the ShareGPT4V dataset, we used translation prompts.
Caption-based prompting:… See the full description on the dataset page: https://huggingface.co/datasets/Vi-VLM/Vista.NExTQAViDoSeektest-grpo-vlm-log-completions
TRL Completion logs
This dataset contains the completions generated during training using trl.
The completions are stored in parquet files, and each file contains the completions for a single step of training (depending on the logging_steps argument).
Each file contains the following columns:
step: the step of training
prompt: the prompt used to generate the completion
completion: the completion generated by the model
<reward_function_name>: the reward(s) assigned to the completion… See the full description on the dataset page: https://huggingface.co/datasets/qgallouedec/test-grpo-vlm-log-completions.MMLongBench-page-fixedViDoSeek-page-fixedtrain_ctf_eeftrain_ctfverl_vla_libero_collectedThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "panda",
"total_episodes": 32,
"total_frames": 2990,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 1e-06,
"fps": 10,
"splits": {
"train": "0:32"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/Miical/verl_vla_libero_collected.test_ctfMVBench
MVBench
Forked from https://huggingface.co/datasets/OpenGVLab/MVBench for reproducibility.
Important Update
[18/10/2024] Due to NTU RGB+D License, 320 videos from NTU RGB+D need to be downloaded manually. Please visit ROSE Lab to access the data. We also provide a list of the 320 videos used in MVBench for your reference.
We introduce a novel static-to-dynamic method for defining temporal-related tasks. By converting static tasks into dynamic ones, we facilitate… See the full description on the dataset page: https://huggingface.co/datasets/VLM2Vec/MVBench.WN18RRvlm-info-loss-results
VLM Grounding Evaluation Results
Grounding evaluation results for vision-language models on robotics manipulation datasets.
Part of the vlm-info-loss project studying
how VLM connectors transform visual representations.
Background
Our embedding-level analysis shows VLM connectors perform a compress-then-expand transformation:
they sharpen dominant-object representations while compressing secondary-object category identity.
All tested models converge to ~83%… See the full description on the dataset page: https://huggingface.co/datasets/MicroAGI-Labs/vlm-info-loss-results.safedocs-cc-2m-paddle-vl-1-6-openrouter-judged
SafeDocs selected corpus: OCR judge annotations
All source rows and columns are preserved, including images and complete Paddle
outputs. Added columns: judge_verdict, judge_reason, judge_status, judge_error.
PERFECT/ERROR are model quality judgments, not verified ground truth.
Operational failures have null verdicts and are distinct from OCR errors.
No pages are filtered. Whole-document filtering and enrichment are downstream.
Muse Spark 1.3 Contributor through OpenRouter, low… See the full description on the dataset page: https://huggingface.co/datasets/albertklorer/safedocs-cc-2m-paddle-vl-1-6-openrouter-judged.Vlaserpixie
Pixie Dataset
This dataset contains data and pre-trained models for the paper Pixie: Fast and Generalizable Supervised Learning of 3D Physics from Pixels.
Project Page: https://pixie-3d.github.io/
Code: https://github.com/vlongle/pixie
Contents
checkpoints_continuous_mse/: Continuous material property prediction model checkpoints
checkpoints_discrete/: Discrete material classification model checkpoints
real_scene_data/: Real scene data for evaluation… See the full description on the dataset page: https://huggingface.co/datasets/vlongle/pixie.cu-vla-exp6-b0-lclickWN18mikasa-robo-vla-lerobotVR-egodex-annotation-converted-v6.0
VR-egodex-annotation-converted-v6.0
EgoDex converted from LeRobot v2.1 into the Layer-1 v0.6.0 annotation schema, with
per-clip narration included as language sidecars.
314,839 clips · 78,282,306 frames · 724.8 hours @ 30 fps · 129 tasks
100% narration coverage (1 sidecar per clip)
71 GB annotations + 2.3 GB narratives
Videos are NOT included. This release contains annotations and narration only. Source
video lives in griffinlabs/EgoDex-LeRobot-v3.0;
orig_id in the manifest… See the full description on the dataset page: https://huggingface.co/datasets/VR-VLA/VR-egodex-annotation-converted-v6.0.2chSTRUCTURE.md — подробности датасета, разбор схемы и семантика форума
⚡ 2ch — Russian Anonymous Imageboard Archive · 2009–2026
Датасет тредов Двача
Total: 1 455 924 threads · 238 479 526 posts
BoardThreadsPostsShare
/b/872 569114 896 80948.18%
/po/225 71035 024 43914.69%
/fag/48 56324 337 45610.21%
/sex/35 5576 611 2842.77%
/news/69 5005 031 2052.11%
/dev/18 4844 310 2051.81%
/mov/8 4463 309 6041.39%
/ftb/5 3242 574 1131.08%
/wm/4 3482 494 5441.05%
/wrk/5 5752 181 8450.91%
/sp/3… See the full description on the dataset page: https://huggingface.co/datasets/vladlinv/2ch.