# Datasets, Page 132 of 132
Source: https://savrn.com/datasets/page/132
Markdown alternate of the page above; the site index is https://savrn.com/llms.txt

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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

- [10K<n<100K125](https://savrn.com/datasets?size=10K%3Cn%3C100K)
- [1K<n<10K106](https://savrn.com/datasets?size=1K%3Cn%3C10K)
- [n<1K100](https://savrn.com/datasets?size=n%3C1K)
- [100K<n<1M70](https://savrn.com/datasets?size=100K%3Cn%3C1M)
- [1M<n<10M51](https://savrn.com/datasets?size=1M%3Cn%3C10M)
- [10M<n<100M33](https://savrn.com/datasets?size=10M%3Cn%3C100M)
- [100M<n<1B21](https://savrn.com/datasets?size=100M%3Cn%3C1B)
- [n>1T16](https://savrn.com/datasets?size=n%3E1T)
- [1B<n<10B8](https://savrn.com/datasets?size=1B%3Cn%3C10B)
- [100B<n<1T5](https://savrn.com/datasets?size=100B%3Cn%3C1T)
- [10B<n<100B2](https://savrn.com/datasets?size=10B%3Cn%3C100B)
- [10GB<n<100GB1](https://savrn.com/datasets?size=10GB%3Cn%3C100GB)
- [120,8981](https://savrn.com/datasets?size=120%2C898)
- [1B-tokens1](https://savrn.com/datasets?size=1B-tokens)
- [1T<n<10T1](https://savrn.com/datasets?size=1T%3Cn%3C10T)
- [n1K<n10K1](https://savrn.com/datasets?size=n1K%3Cn10K)
- [n<100K1](https://savrn.com/datasets?size=n%3C100K)
- [n<10K1](https://savrn.com/datasets?size=n%3C10K)
- [n<1GB1](https://savrn.com/datasets?size=n%3C1GB)
- [n>1M1](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

### [wmw-internal](https://savrn.com/datasets/wmw-internal)

[Nicklas Hansen](https://savrn.com/model-publishers/nicklashansen)

Publicly accessible

[View dataset](https://savrn.com/datasets/wmw-internal)

Dataset

### [wmw-internal-v2](https://savrn.com/datasets/wmw-internal-v2)

[Nicklas Hansen](https://savrn.com/model-publishers/nicklashansen)

Publicly accessible

[View dataset](https://savrn.com/datasets/wmw-internal-v2)

Dataset

### [world-signals](https://savrn.com/datasets/world-signals)

[Kosuke OKADA](https://savrn.com/model-publishers/lilambd)

One folder per day under data/YYYY-MM-DD/, and the same files copied to latest/. Built every morning (JST) by the EmpireOS world model. Nothing is generated by a model; every row is a measurement from a public source. Countries: JP, US, GB, DE, FR, ES, IT, BR, MX, IN, ID, KR, TW, VN, TH, PH, TR, SA, EG, NG, ZA, KE, PL, NL, SE, AU, CA, AR, CO, CL. Agents and analysts keep re-scraping the same public endpoints every day. This dataset does it once, keeps the history, and gives it in one flat shape. GDELT data is free for any use with attribution to the GDELT Project. Google Trends, Apple, GitHub, Hugging Face, Steam and npm data are reproduced as published by their public endpoints; check each…

Publicly accessible cc-by-4.0 1K<n<10K

[View dataset](https://savrn.com/datasets/world-signals)

Dataset

### [world_of_warcraft_bc_01](https://savrn.com/datasets/world-of-warcraft-bc-01)

[Opensima37](https://savrn.com/model-publishers/opensima37)

Publicly accessible

[View dataset](https://savrn.com/datasets/world-of-warcraft-bc-01)

Dataset · Other

### [worldengine-counterfactual-lead-pair-ladder-v9](https://savrn.com/datasets/worldengine-counterfactual-lead-pair-ladder-v9)

[CHEN ZHAN](https://savrn.com/model-publishers/weixicz)

This public dataset contains 65,131 rendered counterfactual cases organized into 8,491 same-history action/future groups. Each case has 4 historical and 8 future CAMF0 frames plus WorldEngine metadata. Archives preserve complete pair groups. The audit bundle contains group JSON manifests, receipts, validation reports and the completion contract. Large generator-intermediate subset PKLs are intentionally excluded because the CAST paired-cache builder consumes the group JSON and rendered frames only. Download all files and run bash extractall.sh DESTINATION. The extraction script verifies every archive against SHA256SUMS first.

Publicly accessible other

[View dataset](https://savrn.com/datasets/worldengine-counterfactual-lead-pair-ladder-v9)

Dataset · Tabular regression

### [worldpop-jp-2026-01](https://savrn.com/datasets/worldpop-jp-2026-01)

[Yui Matsumura](https://savrn.com/model-publishers/yuiseki)

WorldPop's gridded population of Japan, 2015 to 2030, release R2025A: how many people live in every 100 m and every 1 km cell, by sex and five-year age band at 1 km, and the degree of urbanisation of every cell. 1,024 rasters as WorldPop published them, and the same rasters as Cloud Optimized GeoTIFF. CC BY 4.0. Cite each product by its DOI (see Licence). WorldPop's server sends whole files and ignores HTTP Range requests, at about 400 KB/s a connection, and its GeoTIFFs are striped. To look at one city you fetch the country. The COGs here are tiled at 512 with overviews, and the Hub answers Range requests, so GDAL's /vsicurl/ or rasterio can read a window. The files of a release are not…

Publicly accessible cc-by-4.0 1K<n<10K

[View dataset](https://savrn.com/datasets/worldpop-jp-2026-01)

Dataset · Robotics

### [xarm7_pick_orange_ball_large](https://savrn.com/datasets/xarm7-pick-orange-ball-large)

[National Engineering Research Center for Big Data Software](https://savrn.com/model-publishers/thulab)

Apache TsFile version of zwonzis/xarm7-pick-orange-ball-large. A UFactory xArm7 dataset for the task "pick up the orange ball and put it in the cyan bowl". Each frame records the 8-D arm state and the 8-D commanded action. Task (taskindex 0): "pick up the orange ball and put it in the cyan bowl". - Time (INT64, milliseconds) - per-episode sample time, round(timestamp 1000) in milliseconds (the source timestamp column equals Time / 1000 seconds and is therefore not stored separately). - episodeindex, taskindex (TAG) - device dimensions identifying one demonstration episode and one task; query a single episode with WHERE episodeindex=0. - observationstate0..7, action0..7 (FIELD) - FLOAT 8-D…

Publicly accessible apache-2.0 10K<n<100K

[View dataset](https://savrn.com/datasets/xarm7-pick-orange-ball-large)

Dataset

### [xe-dap-dien-co-phai-doi-mu-bao-hiem-khong](https://savrn.com/datasets/xe-dap-dien-co-phai-doi-mu-bao-hiem-khong)

[Xuong san xuat non bao hiem Thang Loi](https://savrn.com/model-publishers/nonbaohiemthangloi)

Publicly accessible

[View dataset](https://savrn.com/datasets/xe-dap-dien-co-phai-doi-mu-bao-hiem-khong)

Dataset

### [xvla-oct26-draft-dataset](https://savrn.com/datasets/xvla-oct26-draft-dataset)

[Sai Tarun Inaganti](https://savrn.com/model-publishers/kindredbluespirit)

Publicly accessible

[View dataset](https://savrn.com/datasets/xvla-oct26-draft-dataset)

Dataset

### [xxd-paper-task-blobs](https://savrn.com/datasets/xxd-paper-task-blobs)

[Steadyworks](https://savrn.com/model-publishers/steadyworks)

Publicly accessible

[View dataset](https://savrn.com/datasets/xxd-paper-task-blobs)

Dataset

### [ycxnk](https://savrn.com/datasets/ycxnk)

[Jingkun Yue](https://savrn.com/model-publishers/chaty123)

Access requested at publisher

[View dataset](https://savrn.com/datasets/ycxnk)

Dataset

### [yds_wip_102026](https://savrn.com/datasets/yds-wip-102026)

[922-Skinaypraeyna](https://savrn.com/model-publishers/922-sy)

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/yds-wip-102026)

Dataset

### [yodas3](https://savrn.com/datasets/yodas3)

[ESPnet](https://savrn.com/model-publishers/espnet)

Publicly accessible cc-by-3.0

[View dataset](https://savrn.com/datasets/yodas3)

Dataset

### [yolo-baselines-no-mosaic-musgd-runs](https://savrn.com/datasets/yolo-baselines-no-mosaic-musgd-runs)

[LeDuy](https://savrn.com/model-publishers/duyle2408)

Publicly accessible

[View dataset](https://savrn.com/datasets/yolo-baselines-no-mosaic-musgd-runs)

Dataset

### [yolov8-seed44-size-eval-runs](https://savrn.com/datasets/yolov8-seed44-size-eval-runs)

[LeDuy](https://savrn.com/model-publishers/duyle2408)

Publicly accessible

[View dataset](https://savrn.com/datasets/yolov8-seed44-size-eval-runs)

Dataset

### [yt2026_batch02_10kh](https://savrn.com/datasets/yt2026-batch02-10kh)

[Tuan](https://savrn.com/model-publishers/salmonai123)

Access requested at publisher

[View dataset](https://savrn.com/datasets/yt2026-batch02-10kh)

Dataset

### [yt2026_batch03_10kh](https://savrn.com/datasets/yt2026-batch03-10kh)

[Tuan](https://savrn.com/model-publishers/salmonai123)

Access requested at publisher

[View dataset](https://savrn.com/datasets/yt2026-batch03-10kh)

Dataset

### [yubi-corl2026-umi-arena-02-2k1](https://savrn.com/datasets/yubi-corl2026-umi-arena-02-2k1)

[AIRoA](https://savrn.com/model-publishers/airoa-org)

Part 2 of 5 of the competition data release yubi-corl2026-umi-arena for The UMI Arena (CoRL 2026), organized by the AI Robot Association (AIRoA). All five parts are covered by the same Limited-Access Dataset Terms of Use; the release identifier in the terms, yubi-corl2026-umi-arena, refers to all five repositories. The center camera video is not included in this release. Access is limited to registered participants of The UMI Arena policy competition: 1. Register for the competition and submit the NDA via the 2. Request access on this page with the same Hugging Face account; requests are approved manually after registration is verified. 3. Questions: umi-arena@airoa.org. source footage were…

Access requested at publisher other 100M<n<1B

[View dataset](https://savrn.com/datasets/yubi-corl2026-umi-arena-02-2k1)

Dataset

### [yubi-corl2026-umi-arena-03-2k0](https://savrn.com/datasets/yubi-corl2026-umi-arena-03-2k0)

[AIRoA](https://savrn.com/model-publishers/airoa-org)

Part 3 of 5 of the competition data release yubi-corl2026-umi-arena for The UMI Arena (CoRL 2026), organized by the AI Robot Association (AIRoA). All five parts are covered by the same Limited-Access Dataset Terms of Use; the release identifier in the terms, yubi-corl2026-umi-arena, refers to all five repositories. The center camera video is not included in this release. Access is limited to registered participants of The UMI Arena policy competition: 1. Register for the competition and submit the NDA via the 2. Request access on this page with the same Hugging Face account; requests are approved manually after registration is verified. 3. Questions: umi-arena@airoa.org. source footage were…

Access requested at publisher other 100M<n<1B

[View dataset](https://savrn.com/datasets/yubi-corl2026-umi-arena-03-2k0)

Dataset · Speech recognition

### [zc](https://savrn.com/datasets/zc)

[Aat](https://savrn.com/model-publishers/aarontseng)

English TTS（語音合成）訓練集 ASR（語音識別）訓練集或測試集 TTS 效果演示：https://huggingface.co/spaces/laubonghaudoi/zoengjyutgaaitts 所有文本都根據 https://jyutping.org/blog/typo/ 同 https://jyutping.org/blog/particles/ 規範用字。 所有音頻源都存放喺/source，為方便直接用作訓練數據，切分後嘅音頻都放喺 opus/ 所有 opus 音頻皆為

Publicly accessible cc0-1.0 10K<n<100K

[View dataset](https://savrn.com/datasets/zc)

## Model Collections

Hand-picked starting points, each with the reason it exists.

Collection · 4 entries

### [Embedding models for retrieval](https://savrn.com/collections/embedding-models-for-retrieval)

Sentence and document embedding models used to build retrieval systems. Dimension and sequence length matter more than size here, and both come from the publisher.

[View collection](https://savrn.com/collections/embedding-models-for-retrieval)

Collection · 4 entries

### [Models that fit on one accelerator](https://savrn.com/collections/models-that-run-on-one-accelerator)

Models whose publisher-reported parameter count puts them within reach of a single accelerator at common precisions. Memory needed depends on precision and serving configuration, so treat the parameter count as the starting point, not the answer.

[View collection](https://savrn.com/collections/models-that-run-on-one-accelerator)

Collection · 6 entries

### [Open-weight text models worth knowing](https://savrn.com/collections/open-weight-text-models-worth-knowing)

Widely used open-weight language models, chosen because each one is a distinct family rather than a variant of the one above it. Selection, not a ranking.

[View collection](https://savrn.com/collections/open-weight-text-models-worth-knowing)

Collection · 3 entries

### [Speech and audio models](https://savrn.com/collections/speech-and-audio)

Recognition and synthesis models, grouped so the two directions are easy to compare.

[View collection](https://savrn.com/collections/speech-and-audio)

## Related SAVRN Research

The hub sits beside SAVRN's market data and infrastructure research: what models cost to run, and what it takes to run them.

SAVRN Index

### [What open models cost to run](https://savrn.com/ai-index/pricing/open-models)

The same open-weight model priced by every host that serves it, per million tokens.

Research Hub

### [Data center trackers and maps](https://savrn.com/data-center-research)

Moratoriums, permits, power, water and capital behind the facilities that run these models.

Method

### [How the Model Hub is built](https://savrn.com/model-hub/methodology)

Sources, evidence labels, refresh behaviour, and the limits of every comparison here.