# Datasets, Page 71 of 132
Source: https://savrn.com/datasets/page/71
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

- [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 · Text generation

### [algorithmic-activism-corpus](https://savrn.com/datasets/algorithmic-activism-corpus)

[Bernhard Springer](https://savrn.com/model-publishers/hardtoneselector)

Synthetische, wertebasierte Erzaehltexte, generiert aus den Allgemeinen Erklaerung der Menschenrechte (UDHR, gemeinfrei) durch ein lokales Sprachmodell (Default qwen2.5:7b via Ollama). output (Erzaehltext), meta (Artikel, Stil, Sprache, Modell, Zeitstempel, Wortzahl, Guardrail-Pruefergebnis). landen im Quarantaene-Ast des Quell-Repositories und werden hier nicht veroeffentlicht. Der Audit ist ein Filter, kein Beweis — Nachpruefung empfohlen.

Publicly accessible cc-by-4.0

[View dataset](https://savrn.com/datasets/algorithmic-activism-corpus)

Dataset · Feature extraction

### [epstein-index](https://savrn.com/datasets/epstein-index)

[Robb Doering](https://savrn.com/model-publishers/robbd)

Machine-readable text of the publicly released Jeffrey Epstein–related document collections: the DOJ "EFTA" disclosures (Data Sets 1–12), House Oversight releases, court records (Maxwell, Doe v. Epstein/Indyke, Florida v. Epstein, USVI v. JPMorgan, and others), and FOIA productions (FBI, BOP, CBP, Florida). All content is public-record material released by the U.S. Department of Justice, federal/state courts, and FOIA respondents. This is a living dataset: this snapshot publishes 32,172 documents — including the full House Oversight estate releases of Oct 17 (8,718 pages) and Nov 12 (22,903 pages); roughly 33,000 source PDFs are downloaded and mid-OCR at snapshot time, with over 1.3M…

Publicly accessible other 10K<n<100K

[View dataset](https://savrn.com/datasets/epstein-index)

Dataset · Text retrieval

### [ipfs_australia_laws_ir](https://savrn.com/datasets/ipfs-australia-laws-ir)

[Justicedao](https://savrn.com/model-publishers/justicedao)

Research retrieval release of endomorphosis/ipfsaustralialaws (revision c72ad1989fc8d4f4858ea8e2944c77f08406a6dd) packaged as country-laws-ir-graphrag/v1 (layout family skillcenter-huggingface-release/v3 / publicus-ir). Not legal advice. This is a research snapshot. The official gazette / authentic source of Australia prevails over this corpus. Retrieved documents and graph edges are retrieval evidence only. No legal text was invented. Primary key: entrycid (CIDv1 raw sha2-256 of a canonical identity record). Integer documentindex values are compact shard pointers, not identities. Target Hub id (packaging metadata only): justicedao/ipfsaustralialawsir. entrycid, lawcid, recordtype…

Publicly accessible other

[View dataset](https://savrn.com/datasets/ipfs-australia-laws-ir)

Dataset

### [Dream.exe](https://savrn.com/datasets/dream-exe)

[Kaiming Yang](https://savrn.com/model-publishers/kaimingyang)

Dream.exe Benchmark Code · DVD checkpoints This release preserves the original 101 benchmark cases. The Dream.exe authors constructed the task instances, frozen scenes, camera settings, generation inputs, and reference data using RoboCasa data and environments. Download and reproduce After completing the code repository's installation guide, run from the code repository root: hf download kaimingyang/Dream.exe --repo-type dataset \ --include 'bench/'

Publicly accessible

[View dataset](https://savrn.com/datasets/dream-exe)

Dataset

### [OpenSeal-SEA-PILE-v2](https://savrn.com/datasets/openseal-sea-pile-v2)

[NUS NLP Group](https://savrn.com/model-publishers/nusnlp)

Publicly accessible

[View dataset](https://savrn.com/datasets/openseal-sea-pile-v2)

Dataset

### [babyvlm-requests](https://savrn.com/datasets/babyvlm-requests)

[BabyVLM Challange](https://savrn.com/model-publishers/babyvlm-challenge)

Publicly accessible

[View dataset](https://savrn.com/datasets/babyvlm-requests)

Dataset

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

[Hoang Thi Trang](https://savrn.com/model-publishers/tranghoang56159)

Publicly accessible

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

Dataset

### [omnilingual-finetune-data](https://savrn.com/datasets/omnilingual-finetune-data)

[Some](https://savrn.com/model-publishers/guruawe)

Publicly accessible

[View dataset](https://savrn.com/datasets/omnilingual-finetune-data)

Dataset

### [synRL-backup](https://savrn.com/datasets/synrl-backup)

[DDY](https://savrn.com/model-publishers/daipath)

Access requested at publisher

[View dataset](https://savrn.com/datasets/synrl-backup)

Dataset · Speech recognition

### [dhravani-mit-test](https://savrn.com/datasets/dhravani-mit-test)

[Shrikant Nayak](https://savrn.com/model-publishers/shrikanth-19)

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference A web-based interface for preparing audio datasets to fine-tune OpenAI's Whisper model. This tool helps in recording, managing, and organizing voice recordings with their corresponding transcriptions, with support for cloud storage and authentication. - ⌨ Keyboard shortcuts for efficiency 1. Create a transcript CSV file with your content: 2. Start the Flask application: 3. Access the interface: 1. Authentication 2. Session Setup - Click "Start Session" 3. Recording - Use on-screen controls or keyboard shortcuts: - R: Start recording / Stop recording - Space: Play recording - Enter: Save…

Publicly accessible cc-by-4.0

[View dataset](https://savrn.com/datasets/dhravani-mit-test)

Dataset

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

[Emma Graham Griffin](https://savrn.com/model-publishers/emmagriffin95052)

Publicly accessible

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

Dataset

### [20261006_VR_H5D_VFE_sim_infer_pick_success](https://savrn.com/datasets/20261006-vr-h5d-vfe-sim-infer-pick-success)

[Nguyen Quang Tan](https://savrn.com/model-publishers/tt1225)

Publicly accessible

[View dataset](https://savrn.com/datasets/20261006-vr-h5d-vfe-sim-infer-pick-success)

Dataset · Speech recognition

### [dhravani-iitpatna-test](https://savrn.com/datasets/dhravani-iitpatna-test)

[Shrikant Nayak](https://savrn.com/model-publishers/shrikanth-19)

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference A web-based interface for preparing audio datasets to fine-tune OpenAI's Whisper model. This tool helps in recording, managing, and organizing voice recordings with their corresponding transcriptions, with support for cloud storage and authentication. - ⌨ Keyboard shortcuts for efficiency 1. Create a transcript CSV file with your content: 2. Start the Flask application: 3. Access the interface: 1. Authentication 2. Session Setup - Click "Start Session" 3. Recording - Use on-screen controls or keyboard shortcuts: - R: Start recording / Stop recording - Space: Play recording - Enter: Save…

Publicly accessible cc-by-4.0

[View dataset](https://savrn.com/datasets/dhravani-iitpatna-test)

Dataset

### [indic-asr-staging-shard12](https://savrn.com/datasets/indic-asr-staging-shard12)

[SAJAL MADAN](https://savrn.com/model-publishers/sajalmadan09)

Publicly accessible

[View dataset](https://savrn.com/datasets/indic-asr-staging-shard12)

Dataset

### [radiotelescope](https://savrn.com/datasets/radiotelescope-2)

[Pham Thi Thao](https://savrn.com/model-publishers/thaopham81807)

Publicly accessible

[View dataset](https://savrn.com/datasets/radiotelescope-2)

Dataset · Object detection

### [tracking_anything_datasets](https://savrn.com/datasets/tracking-anything-datasets)

[Wen](https://savrn.com/model-publishers/jeffry77)

Release: tracking-anything-native-corpora-20261004. Upload: IN PROGRESS — do not treat partial uploads as a complete dataset. Original native archive/annotation mirror, not converted conversations or model-generated labels. No model weights, V8 memory cache, credentials, cookies, or runtime logs are included. This is not a strictly train-only export. TNL2K/VastTrack standalone test archives are excluded; LaSOT and TNLLT originals contain both train and test. COCO train2014 includes images used by REFER training, validation and test expressions. Use the original published splits; never train indiscriminately on every archive member. The small official TNL2K four-video patch also contains one…

Publicly accessible other

[View dataset](https://savrn.com/datasets/tracking-anything-datasets)

Dataset

### [Virtual4DSG](https://savrn.com/datasets/virtual4dsg)

[Zzae](https://savrn.com/model-publishers/jaewonbae)

Publicly accessible

[View dataset](https://savrn.com/datasets/virtual4dsg)

Dataset

### [WebShop-Qwen3-8B-SEED-nostd-s1000-eval](https://savrn.com/datasets/webshop-qwen3-8b-seed-nostd-s1000-eval)

[Cyrus Kwan](https://savrn.com/model-publishers/wckwan)

Publicly accessible

[View dataset](https://savrn.com/datasets/webshop-qwen3-8b-seed-nostd-s1000-eval)

Dataset

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

[Ho Quang Khoa](https://savrn.com/model-publishers/khoaho47995)

Publicly accessible

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

Dataset

### [kairo-dataset](https://savrn.com/datasets/kairo-dataset)

[Kairo](https://savrn.com/model-publishers/kairo-crypto-model)

Every page in this dataset was read by a Kairo spider in a real browser (watch them live at https://kairollm.live), cleaned (menus/footers removed), checked for crypto relevance and deduplicated (SHA-256 + SimHash). It is updated automatically while the spiders work, and each Kairo model version names the exact revision of this dataset it was trained on. id (increasing), url, domain, chapter, title, text, tokens (approximate), crawledat (ms). Pages keep the copyright of their original sites; this dataset is shared for research.

Publicly accessible other

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

Dataset

### [Terania_20260522_20260925](https://savrn.com/datasets/terania-20260522-20260925)

[Marco Lassandro](https://savrn.com/model-publishers/frogpod)

Publicly accessible

[View dataset](https://savrn.com/datasets/terania-20260522-20260925)

Dataset · Image feature extraction

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

[NeuroSpin/GAIA](https://savrn.com/model-publishers/neurospin)

Preprocessed versions of the OpenMind dataset (Wald et al., 2025): head & neck 3D MRI pooled from ~800 OpenNeuro datasets. Here the brain T1w, T2w and FLAIR images were preprocessed at using brainprep and packed as WebDataset shards, ready for large-scale (e.g. self-supervised) deep learning. All folders share the same sample identifiers: (datasetid, subject, session, run), with datasetid the shard folder name, so derivatives of the same scan can be joined across folders. Each preprocessing folder holds one folder of WebDataset shards per OpenNeuro dataset and an index.json.gz with the byte offsets of every file of the shards, used by nidl for random access. valsplit.csv (columns datasetid…

Publicly accessible cc-by-4.0 10K<n<100K

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

Dataset

### [geo-res-big04_full](https://savrn.com/datasets/geo-res-big04-full)

[Roger Q](https://savrn.com/model-publishers/yyt-t)

Publicly accessible

[View dataset](https://savrn.com/datasets/geo-res-big04-full)

Dataset

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

[Kar Kor](https://savrn.com/model-publishers/k4rk0or)

Publicly accessible

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

## 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.