# Datasets, Page 130 of 132 Source: https://savrn.com/datasets/page/130 Markdown alternate of the page above; the site index is https://savrn.com/llms.txt --- SAVRN Model Hub # AI Training Datasets Each dataset with its card, its structure (every split, row count and column type), its files, its license, and the models that disclose training on it. 11,122Models 3,164Datasets 285Papers 6,792Publishers 11,852Sourced relationships Updated 2026-10-18 · [How the library is built](https://savrn.com/model-hub/methodology) ## Filter Datasets Task - [Text generation127](https://savrn.com/datasets?task=Text+generation) - [Robotics106](https://savrn.com/datasets?task=Robotics) - [Other48](https://savrn.com/datasets?task=Other) - [Text classification47](https://savrn.com/datasets?task=Text+classification) - [Text retrieval44](https://savrn.com/datasets?task=Text+retrieval) - [Question answering36](https://savrn.com/datasets?task=Question+answering) - [Speech recognition33](https://savrn.com/datasets?task=Speech+recognition) - [Tabular classification21](https://savrn.com/datasets?task=Tabular+classification) - [Time series forecasting21](https://savrn.com/datasets?task=Time+series+forecasting) - [Image to text17](https://savrn.com/datasets?task=Image+to+text) - [Image classification16](https://savrn.com/datasets?task=Image+classification) - [Object detection14](https://savrn.com/datasets?task=Object+detection) - [Text to speech14](https://savrn.com/datasets?task=Text+to+speech) - [Visual question answering14](https://savrn.com/datasets?task=Visual+question+answering) - [Image to image11](https://savrn.com/datasets?task=Image+to+image) - [Image segmentation9](https://savrn.com/datasets?task=Image+segmentation) - [Image to 3d9](https://savrn.com/datasets?task=Image+to+3d) - [Translation9](https://savrn.com/datasets?task=Translation) - [Video classification9](https://savrn.com/datasets?task=Video+classification) - [Audio classification7](https://savrn.com/datasets?task=Audio+classification) - [Feature extraction7](https://savrn.com/datasets?task=Feature+extraction) - [Reinforcement learning7](https://savrn.com/datasets?task=Reinforcement+learning) - [Text to image7](https://savrn.com/datasets?task=Text+to+image) - [Text to video7](https://savrn.com/datasets?task=Text+to+video) License - [other250](https://savrn.com/datasets?license=other) - [apache-2.0236](https://savrn.com/datasets?license=apache-2.0) - [mit232](https://savrn.com/datasets?license=mit) - [cc-by-4.0224](https://savrn.com/datasets?license=cc-by-4.0) - [cc-by-nc-4.077](https://savrn.com/datasets?license=cc-by-nc-4.0) - [cc0-1.030](https://savrn.com/datasets?license=cc0-1.0) - [cc-by-sa-4.029](https://savrn.com/datasets?license=cc-by-sa-4.0) - [odc-by24](https://savrn.com/datasets?license=odc-by) - [cc-by-nc-sa-4.020](https://savrn.com/datasets?license=cc-by-nc-sa-4.0) - [unknown14](https://savrn.com/datasets?license=unknown) - [cc-by-sa-3.06](https://savrn.com/datasets?license=cc-by-sa-3.0) - [odbl6](https://savrn.com/datasets?license=odbl) - [gpl-3.05](https://savrn.com/datasets?license=gpl-3.0) - [cc-by-3.04](https://savrn.com/datasets?license=cc-by-3.0) - [cc3](https://savrn.com/datasets?license=cc) - [cc-by-nc-nd-4.03](https://savrn.com/datasets?license=cc-by-nc-nd-4.0) - [gpl3](https://savrn.com/datasets?license=gpl) - [cc-by-2.02](https://savrn.com/datasets?license=cc-by-2.0) - [cc-by-nd-4.02](https://savrn.com/datasets?license=cc-by-nd-4.0) - [cdla-sharing-1.02](https://savrn.com/datasets?license=cdla-sharing-1.0) - [agpl-3.01](https://savrn.com/datasets?license=agpl-3.0) - [bsl-1.01](https://savrn.com/datasets?license=bsl-1.0) - [c-uda1](https://savrn.com/datasets?license=c-uda) - [cc-by-nc-3.01](https://savrn.com/datasets?license=cc-by-nc-3.0) Access - [Publicly accessible2,933](https://savrn.com/datasets?access=open_access) - [Access requested at publisher231](https://savrn.com/datasets?access=gated) Publisher - [Benjamin J Barber35](https://savrn.com/datasets?publisher=endomorphosis) - [Chang Yu24](https://savrn.com/datasets?publisher=g1n0st) - [Ji Xie23](https://savrn.com/datasets?publisher=sanaka87) - [Justicedao18](https://savrn.com/datasets?publisher=justicedao) - [LeDuy13](https://savrn.com/datasets?publisher=duyle2408) - [Nguyen13](https://savrn.com/datasets?publisher=icdn11) - [Nguyen13](https://savrn.com/datasets?publisher=icdn12) - [Nguyen13](https://savrn.com/datasets?publisher=icdn13) - [National Engineering Research Center for Big Data Software13](https://savrn.com/datasets?publisher=thulab) - [Nguyen12](https://savrn.com/datasets?publisher=icdn10) - [Nguyen12](https://savrn.com/datasets?publisher=icdn14) - [Byte I12](https://savrn.com/datasets?publisher=icdn15) - [Rebrowser.net12](https://savrn.com/datasets?publisher=rebrowser) - [Shufan Jiang12](https://savrn.com/datasets?publisher=tsumugii) - [Ai210](https://savrn.com/datasets?publisher=allenai) - [Ps Yo10](https://savrn.com/datasets?publisher=atokforps) - [Dougall DeepMind10](https://savrn.com/datasets?publisher=dougalldeepmind) - [Deesced9](https://savrn.com/datasets?publisher=ameluce) - [Jiahao Zhang9](https://savrn.com/datasets?publisher=hi-todayis-jh) - [Julia Dollis9](https://savrn.com/datasets?publisher=juliadollis) - [Massive Text Embedding Benchmark9](https://savrn.com/datasets?publisher=mteb) - [Pranab Pattanaik9](https://savrn.com/datasets?publisher=p2samapa) - [Sota9](https://savrn.com/datasets?publisher=sotaagi2030) - [Sunsetcanyon9](https://savrn.com/datasets?publisher=sunsetcanyon) Size - [10K1T16](https://savrn.com/datasets?size=n%3E1T) - [1B1M1](https://savrn.com/datasets?size=n%3E1M) Domain - [LeRobot31](https://savrn.com/datasets?domain=LeRobot) - [legal, law, graphrag12](https://savrn.com/datasets?domain=legal%2C+law%2C+graphrag) - [tsfile, timeseries, time-series12](https://savrn.com/datasets?domain=tsfile%2C+timeseries%2C+time-series) - [open-data, data-science, web-scraping9](https://savrn.com/datasets?domain=open-data%2C+data-science%2C+web-scraping) - [seo-cluster, web-nodes9](https://savrn.com/datasets?domain=seo-cluster%2C+web-nodes) - [dpo, rlhf, ultrafeedback8](https://savrn.com/datasets?domain=dpo%2C+rlhf%2C+ultrafeedback) - [mteb, text, image7](https://savrn.com/datasets?domain=mteb%2C+text%2C+image) - [nepali, instruction-tuning, agriculture7](https://savrn.com/datasets?domain=nepali%2C+instruction-tuning%2C+agriculture) - [science, stackexchange, provenance5](https://savrn.com/datasets?domain=science%2C+stackexchange%2C+provenance) - [LeRobot, robotics, lerobot4](https://savrn.com/datasets?domain=LeRobot%2C+robotics%2C+lerobot) - [ml-intern4](https://savrn.com/datasets?domain=ml-intern) - [AMASS, Retarget, Robotics3](https://savrn.com/datasets?domain=AMASS%2C+Retarget%2C+Robotics) - [benchmark, agents, terminal3](https://savrn.com/datasets?domain=benchmark%2C+agents%2C+terminal) - [climate3](https://savrn.com/datasets?domain=climate) - [code3](https://savrn.com/datasets?domain=code) - [crypto, cryptocurrency, finance3](https://savrn.com/datasets?domain=crypto%2C+cryptocurrency%2C+finance) - [data-attribution, influence-functions, interpretability3](https://savrn.com/datasets?domain=data-attribution%2C+influence-functions%2C+interpretability) - [fireviewer, fire, smoke3](https://savrn.com/datasets?domain=fireviewer%2C+fire%2C+smoke) - [video3](https://savrn.com/datasets?domain=video) - [LeRobot, lerobot, grabette2](https://savrn.com/datasets?domain=LeRobot%2C+lerobot%2C+grabette) - [LeRobot, ur7e, robotiq2](https://savrn.com/datasets?domain=LeRobot%2C+ur7e%2C+robotiq) - [agentenv, rl-environment, agents2](https://savrn.com/datasets?domain=agentenv%2C+rl-environment%2C+agents) - [ai-governance, measurement2](https://savrn.com/datasets?domain=ai-governance%2C+measurement) - [autonomous, agents, evolution2](https://savrn.com/datasets?domain=autonomous%2C+agents%2C+evolution) [Most downloaded](https://savrn.com/datasets?sort=downloads)[Most liked](https://savrn.com/datasets?sort=likes)[Recently updated](https://savrn.com/datasets?sort=updated)[Name](https://savrn.com/datasets?sort=name) 3,164 datasets, sorted by most downloaded. Dataset · Image to text ### [trade-file-completion](https://savrn.com/datasets/trade-file-completion) [Andy Kiro](https://savrn.com/model-publishers/andykiro123234456) Curated multimodal vision dataset of 1-minute candlestick chart captures with technical indicators and verified trade outcomes (WIN / LOSS). This dataset strictly adheres to the official Hugging Face ImageFolder standard: - train/metadata.jsonl: Single-format JSONL metadata with sample annotations - train/images/.jpg: Candlestick chart captures Publicly accessible mit n<1K [View dataset](https://savrn.com/datasets/trade-file-completion) Dataset ### [train3_ver2](https://savrn.com/datasets/train3-ver2) [Thanh](https://savrn.com/model-publishers/pepernamek) Publicly accessible [View dataset](https://savrn.com/datasets/train3-ver2) Dataset ### [travel-pointcloud-text-benchmark](https://savrn.com/datasets/travel-pointcloud-text-benchmark) [Hanna C. Lewandowski](https://savrn.com/model-publishers/hannalewandowski) This repository contains a preparation pipeline and a small metadata sample for Travel work with Pointcloud Text inputs. It does not claim to be a complete benchmark release; the loader documents how source data is normalized and validated. - loaddata.py — loading, cleaning, and split preparation code. - datasetinfos.json — schema and split metadata. - metadatasample.jsonl — small, human-readable records for checking the schema. - README.md — data card and usage notes. Before using the prepared data, verify source licenses, duplicates across splits, missing values, label balance, and modality-specific corruption. Record the source version and every filtering rule so a later run can… Publicly accessible apache-2.0 [View dataset](https://savrn.com/datasets/travel-pointcloud-text-benchmark) Dataset · Image classification ### [tree_species_classification_slovak_normal_cropped](https://savrn.com/datasets/tree-species-classification-slovak-normal-cropped) [AgML](https://savrn.com/model-publishers/project-agml) This dataset provides real RGB images of tree species collected in natural field environments across Slovakia and the Czech Republic. Images were captured using handheld cameras (Sony Alpha 7 and Canon EOS 4000D) during field surveys in June and August 2022. The dataset contains 1,367 images across 4 classes: European beech, European silver fir, Norway spruce, Sessile oak. This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. This dataset was reformatted from its original format to match HuggingFace standards. Publicly accessible cc-by-4.0 1K view.replay, then open view.replay at https://game.battlecode.au/visualiser. manifest.json records archive sizes, SHA256 hashes and game counts. Archive names are unique across the… Publicly accessible [View dataset](https://savrn.com/datasets/unswbc-public-replays) Dataset ### [ur5e-cylinder-3cam-add1005](https://savrn.com/datasets/ur5e-cylinder-3cam-add1005) [Shohei Sato](https://savrn.com/model-publishers/indojin) Publicly accessible [View dataset](https://savrn.com/datasets/ur5e-cylinder-3cam-add1005) Dataset · Robotics ### [ur7_b_into_a_48h_w1_p04](https://savrn.com/datasets/ur7-b-into-a-48h-w1-p04) [Anuj Zore](https://savrn.com/model-publishers/zeroanuj) This dataset was created using LeRobot. Part B (a white disc with a hub and a bar) is found with the wrist camera, picked from the plate and seated into fixture A. Universal Robots UR7e, Robotiq gripper, wrist-mounted Intel RealSense D405. Collected autonomously during a continuous 48-hour run that started on 2026-10-10, to cover the lighting changes of day and night. This repository is one part of that run: 101 episodes, 65387 frames at 30 fps. - State and action (16 values each): 6 joint angles, TCP position, TCP orientation (6D), gripper position. Also recorded: joint velocity, torque and current, TCP force, raw force/torque wrench, gripper effort, capture time. - The wrist camera is… Publicly accessible [View dataset](https://savrn.com/datasets/ur7-b-into-a-48h-w1-p04) Dataset · Robotics ### [ur7_b_into_a_48h_w2_p04](https://savrn.com/datasets/ur7-b-into-a-48h-w2-p04) [Anuj Zore](https://savrn.com/model-publishers/zeroanuj) This dataset was created using LeRobot. Part B (a white disc with a hub and a bar) is found with the wrist camera, picked from the plate and seated into fixture A. Universal Robots UR7e, Robotiq gripper, wrist-mounted Intel RealSense D405. Collected autonomously during a continuous 48-hour run that started on 2026-10-10, to cover the lighting changes of day and night. This repository is one part of that run: 100 episodes, 64553 frames at 30 fps. - State and action (16 values each): 6 joint angles, TCP position, TCP orientation (6D), gripper position. Also recorded: joint velocity, torque and current, TCP force, raw force/torque wrench, gripper effort, capture time. - The wrist camera is… Publicly accessible [View dataset](https://savrn.com/datasets/ur7-b-into-a-48h-w2-p04) Dataset ### [ur7_b_into_a_48h_w3_p04](https://savrn.com/datasets/ur7-b-into-a-48h-w3-p04) [Anuj Zore](https://savrn.com/model-publishers/zeroanuj) Publicly accessible [View dataset](https://savrn.com/datasets/ur7-b-into-a-48h-w3-p04) Dataset · Time series forecasting ### [urban-event-chains](https://savrn.com/datasets/urban-event-chains) [Bibek Gupta](https://savrn.com/model-publishers/bibekgupta3333) Data and results for Multi-Agent Prompting with In-Context Feedback for Cross-Modal Urban Event Chain Prediction (Sensors, MDPI). Code: github.com/bibekgupta3333/urban-event-chain-prediction-multi-agent-prompting The nine -bedrock- run directories are the model grid the paper reports: 5 configurations (singleagent, multiagent, noisysingle, multifeedback, multinofeedback) × expert prompt level × 3 cities, 85 test chains per configuration. Bedrock exposes no seed, so these runs are not byte-reproducible. - Traffic data are municipal traffic-speed feeds (probe-derived segment estimates, daily) — Chicago Traffic Tracker (sxs8-h27x), NYC Real-Time Traffic Speed (i4gi-tjb9), SF via DataSF. They… Publicly accessible other 1M