# Datasets, Page 123 of 132
Source: https://savrn.com/datasets/page/123
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

### [pgsoft1052](https://savrn.com/datasets/pgsoft1052)

[Bapter](https://savrn.com/model-publishers/bobpat2q)

Publicly accessible

[View dataset](https://savrn.com/datasets/pgsoft1052)

Dataset

### [pgsoft1053](https://savrn.com/datasets/pgsoft1053)

[Bapter](https://savrn.com/model-publishers/bobpat2q)

Publicly accessible

[View dataset](https://savrn.com/datasets/pgsoft1053)

Dataset

### [pgsoft1054](https://savrn.com/datasets/pgsoft1054)

[Bapter](https://savrn.com/model-publishers/bobpat2q)

Publicly accessible

[View dataset](https://savrn.com/datasets/pgsoft1054)

Dataset

### [pgsoft1055](https://savrn.com/datasets/pgsoft1055)

[Bapter](https://savrn.com/model-publishers/bobpat2q)

Publicly accessible

[View dataset](https://savrn.com/datasets/pgsoft1055)

Dataset

### [pgsoft1056](https://savrn.com/datasets/pgsoft1056)

[Bapter](https://savrn.com/model-publishers/bobpat2q)

Publicly accessible

[View dataset](https://savrn.com/datasets/pgsoft1056)

Dataset

### [phase4-drafter-lora](https://savrn.com/datasets/phase4-drafter-lora)

[Sharma](https://savrn.com/model-publishers/arushhh)

Publicly accessible

[View dataset](https://savrn.com/datasets/phase4-drafter-lora)

Dataset

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

[A](https://savrn.com/model-publishers/grenico)

Publicly accessible

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

Dataset

### [physam4d-dynamics-checkpoints](https://savrn.com/datasets/physam4d-dynamics-checkpoints)

[QiuyiDing](https://savrn.com/model-publishers/bdxxn)

Publicly accessible

[View dataset](https://savrn.com/datasets/physam4d-dynamics-checkpoints)

Dataset · Robotics

### [pick_and_place_20260923_124542](https://savrn.com/datasets/pick-and-place-20260923-124542)

[An Youngjun](https://savrn.com/model-publishers/sweetofu)

This dataset was created using LeRobot. Dataset Structure "codebaseversion": "v3.0", "fps": 30, "features": { "action": { "dtype": "float32", "names": [ "shoulderpan.pos", "shoulderlift.pos", "elbowflex.pos", "wristflex.pos", "wristroll.pos", "gripper.pos" "shape": [ 6

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/pick-and-place-20260923-124542)

Dataset

### [pick_and_place_4](https://savrn.com/datasets/pick-and-place-4)

[Jun Park](https://savrn.com/model-publishers/jun226)

Publicly accessible

[View dataset](https://savrn.com/datasets/pick-and-place-4)

Dataset

### [pick_and_place_clean_4096](https://savrn.com/datasets/pick-and-place-clean-4096)

[Kaijunluo](https://savrn.com/model-publishers/keith-luo)

Publicly accessible

[View dataset](https://savrn.com/datasets/pick-and-place-clean-4096)

Dataset · Robotics

### [pickup_carrot_remove_parquet_metadata_2](https://savrn.com/datasets/pickup-carrot-remove-parquet-metadata-2)

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

Apache TsFile version of argus-systems/pickup-carrot-remove-parquet-metadata-2. A Trossen AI stationary-arm dataset for a single pick-and-place task: pick up a carrot and put it in the bowl. Each frame records the 14-D dual-arm action and 14-D observation state. Task (taskindex 0): "Pick up carrot and put it in the bowl". Note: the source meta/info.json and meta/episodes.jsonl declare 61 episodes / 27,261 frames, but the source repository only contains 58 data/chunk-000/episode.parquet files (episodes 0, 39 and 50 are absent); the 58 present episodes (25,922 frames) were converted. - Time (INT64, milliseconds) - per-episode sample time, round(timestamp 1000) in milliseconds (the source…

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

[View dataset](https://savrn.com/datasets/pickup-carrot-remove-parquet-metadata-2)

Dataset

### [pjf-escenas](https://savrn.com/datasets/pjf-escenas)

[Pablo Javier Fernandez](https://savrn.com/model-publishers/pablojf77)

Publicly accessible

[View dataset](https://savrn.com/datasets/pjf-escenas)

Dataset

### [plain-drift-2a2d9310be](https://savrn.com/datasets/plain-drift-2a2d9310be)

[Jimmy Chern](https://savrn.com/model-publishers/moonmonster)

Publicly accessible

[View dataset](https://savrn.com/datasets/plain-drift-2a2d9310be)

Dataset · Robotics

### [play_hri_cube_hr_1](https://savrn.com/datasets/play-hri-cube-hr-1)

[Hyeonho Oh](https://savrn.com/model-publishers/leehakho)

This dataset was created using LeRobot.

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/play-hri-cube-hr-1)

Dataset · Robotics

### [play_hri_cube_hr_1_eef](https://savrn.com/datasets/play-hri-cube-hr-1-eef)

[Hyeonho Oh](https://savrn.com/model-publishers/leehakho)

This dataset was created using LeRobot.

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/play-hri-cube-hr-1-eef)

Dataset

### [point-interventions-s64-full-20261005-v1](https://savrn.com/datasets/point-interventions-s64-full-20261005-v1)

[ZY_Liu](https://savrn.com/model-publishers/rookiesjtu)

Publicly accessible

[View dataset](https://savrn.com/datasets/point-interventions-s64-full-20261005-v1)

Dataset

### [pointdit_half_sampling](https://savrn.com/datasets/pointdit-half-sampling)

[Jinlong Li](https://savrn.com/model-publishers/tyronedragon)

Publicly accessible

[View dataset](https://savrn.com/datasets/pointdit-half-sampling)

Dataset · Text classification

### [polyglot-bug-patterns](https://savrn.com/datasets/polyglot-bug-patterns)

[Kicaulah](https://savrn.com/model-publishers/kicaulah)

Bro, imagine a dataset of 43 non-destructive attack payloads across 8 bug classes — 24 of them polyglot, meaning a single string that's simultaneously plausible HTML, JS, SQL and shell, so it escapes whatever context your app dropped it into. Plus real detector output from a full multimodal scan. Everything here is synthesised or locally generated. No real-world traffic, no scraped data, no user data. Each config ships JSONL and Parquet, so both of these work: Every payload carries a unique marker (PBHX7) so reflection is unambiguous — that's what makes these usable as training signal for a detector or as a fixture in your own test suite. This is a defensive dataset. Concretely: Every…

Publicly accessible mit n<1K

[View dataset](https://savrn.com/datasets/polyglot-bug-patterns)

Dataset

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

[H](https://savrn.com/model-publishers/halfman946)

Publicly accessible apache-2.0

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

Dataset

### [pre2post-chess-replication](https://savrn.com/datasets/pre2post-chess-replication)

[ML-Intern-lab](https://savrn.com/model-publishers/ml-intern-lab)

Publicly accessible

[View dataset](https://savrn.com/datasets/pre2post-chess-replication)

Dataset

### [probe-activations-olmo3-7b-think](https://savrn.com/datasets/probe-activations-olmo3-7b-think)

[Utkarsh Khanna](https://savrn.com/model-publishers/utkarshk07)

Publicly accessible

[View dataset](https://savrn.com/datasets/probe-activations-olmo3-7b-think)

Dataset · Text retrieval

### [product-search-rag-data](https://savrn.com/datasets/product-search-rag-data)

[Ian Gault](https://savrn.com/model-publishers/gaultian)

Processed data and prebuilt search indexes for the Product Search RAG app. This repository hosts build artifacts for that app, not a general-purpose dataset. The app downloads these files at startup, since they are too large to keep in its git repository. Derived from the Appliances category of the Amazon Reviews 2023 dataset collected by McAuley Lab. Use of this data follows the terms of the original dataset. Please cite the original authors: parentasin, producttitle, features, description, categories, details, price, derivedavgrating, nreviews, reviewtext, candidatereviewtitle, candidatereviewtext, candidatereviewhelpfulvote See the project repository for the full pipeline (make process…

Publicly accessible other 10K<n<100K

[View dataset](https://savrn.com/datasets/product-search-rag-data)

Dataset

### [product_recommendation_embedding](https://savrn.com/datasets/product-recommendation-embedding)

[Alvaro Danko](https://savrn.com/model-publishers/allvarete)

Publicly accessible

[View dataset](https://savrn.com/datasets/product-recommendation-embedding)

## 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.