# Datasets, Page 43 of 132
Source: https://savrn.com/datasets/page/43
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

### [xuahyja-text](https://savrn.com/datasets/xuahyja-text)

[Raymondt](https://savrn.com/model-publishers/raymondt)

Access requested at publisher

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

Dataset

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

[Vu Minh Phuong](https://savrn.com/model-publishers/phuongvu25662)

Publicly accessible

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

Dataset

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

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

Wikipedia has hundreds of "... by country" articles. The numbers live inside article tables, keyed by country names that differ from article to article. This dataset re-keys every such table to ISO2 so they join. One CSV per source article under tables/. Columns: iso2, country,. Values are kept exactly as printed (num twin columns hold the parsed number where one could be read). index.csv lists every table with its source article, revision id, row count and last change. Built by an autonomous seeker: it lists the articles, reads the tables, matches the country column against a 1,000-name gazetteer (Wikidata labels + aliases), keeps tables with ≥40 matched countries, and re-reads an article…

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

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

Dataset

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

[Abhishek Saha](https://savrn.com/model-publishers/abhishek-a0)

Publicly accessible

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

Dataset

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

[Ryan Lewis](https://savrn.com/model-publishers/gortmankahalehoevwrqw3371733757274)

Publicly accessible

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

Dataset

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

[Vu Hai Yen](https://savrn.com/model-publishers/yenvu35420)

Publicly accessible

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

Dataset

### [file-storage-7485](https://savrn.com/datasets/file-storage-7485)

[How Okd R](https://savrn.com/model-publishers/xhowold)

This dataset is used for file storage purposes. This dataset contains uploaded files organized in the uploads directory.

Publicly accessible mit

[View dataset](https://savrn.com/datasets/file-storage-7485)

Dataset

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

[Kaikai](https://savrn.com/model-publishers/sven1985)

Publicly accessible

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

Dataset · Feature extraction

### [WSI_Embedding](https://savrn.com/datasets/wsi-embedding)

[Than Minh](https://savrn.com/model-publishers/thanminh01)

Patch and slide embeddings for whole-slide images, plus the run records used to produce them. Original WSIs are not in this repo. They stay on HPC / the source dataset remotes. Do not expect.svs /.tif here. Selective download: pull only embeddings/DHMC-LUAD/titan/... or only Run-Information/prep/TCGA-LUAD. There are two HPC job directories. They are not duplicates of the same run: Use DHMC-LUAD for current coords, masks, and later-model logs. Use DHMC-LUAD-TITAN-CONCH for the original TITAN/CONCH job (SLURM 15450381 / 15450382). Kept encoders (see per-model folders under embeddings/DHMC-LUAD/): TITAN 768, CONCH v1.5 768, CONCH v1 512, Virchow 2560, PRISM 1280, Virchow2 2560, Virchow2 CLS…

Publicly accessible 1K<n<10K

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

Dataset

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

[Hoang Hai Khoa](https://savrn.com/model-publishers/khoahoang22009)

Publicly accessible

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

Dataset

### [faers_bronze_demo](https://savrn.com/datasets/faers-bronze-demo)

[João Tiago Viegas](https://savrn.com/model-publishers/jtviegas)

Publicly accessible

[View dataset](https://savrn.com/datasets/faers-bronze-demo)

Dataset

### [HF006](https://savrn.com/datasets/hf006)

[Waycou Koran](https://savrn.com/model-publishers/store06)

Publicly accessible

[View dataset](https://savrn.com/datasets/hf006)

Dataset · Other

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

[Rebrowser.net](https://savrn.com/model-publishers/rebrowser)

prettyname: "CarGurus.com US Vehicle Listings Dataset" - open-data - data-science - web-scraping - scraper - crawler - data-collection - used-cars - automotive - car-listings - vehicle-data - car-prices - cargurus - cargurus-com sizecategories: taskcategories: - other - configname: car-listings datafiles: Daily sample of U.S. used car listings from CarGurus.com with deal ratings, vehicle specs, mileage, dealer info, and market positioning data. This dataset is a preview sample of the CarGurus.com (US) dataset published by Rebrowser. If you're doing academic research, you may be eligible for free access to a much larger slice — see Free Datasets for Research. This dataset contains 1 entity…

Publicly accessible cc-by-nc-4.0 10M<n<100M

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

Dataset

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

[Abigail Keith Ramirez](https://savrn.com/model-publishers/abigailramirez79652)

Publicly accessible

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

Dataset

### [synkrisnew2](https://savrn.com/datasets/synkrisnew2)

[Kgshop](https://savrn.com/model-publishers/kgshop)

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/synkrisnew2)

Dataset · Translation

### [xone-repository-parallel-en-id-corpus](https://savrn.com/datasets/xone-repository-parallel-en-id-corpus)

[Lumina Moon](https://savrn.com/model-publishers/cloverx-id)

We are currently developing new version of LMSE translation scoring model and processing additional data sources. We estimate the dataset will expand, with significantly improved quality.(Delayed..) A score of 55% and above indicates high-quality translation pairs, even if the first version of the model we developed gave them such a score. We will try to release a newer model in the future with better quality and consistently fast scoring speeds, and release it to the public once we decide that this model is ready to be published. The Xone Parallel English-Indonesian Corpus is a large-scale parallel corpus containing over 70 million raw sentence pairs compiled from 11 translation datasets.…

Publicly accessible apache-2.0 100M<n<1B

[View dataset](https://savrn.com/datasets/xone-repository-parallel-en-id-corpus)

Dataset

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

[hGPJYser](https://savrn.com/model-publishers/hgpjyser)

Publicly accessible

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

Dataset

### [sim-training](https://savrn.com/datasets/sim-training)

[LabOS Sim](https://savrn.com/model-publishers/labos-sim)

The categories are success, vortexoff, tubeempty, capopen, tubedrop, wrongorientation, wrongrack, and rackflipped. Use progress.json and pipelinestatus.json for the current generation status. GENERATIONCOMPLETE.json is created only after final extension validation. Do not infer completeness from the folder name. Each CATEGORY/sceneNNNNNN/ contains three synchronized videos (left.mp4, front.mp4, right.mp4), matching per-video JSON metadata, metadata.json, sharedstate.npz, and three QA contact sheets. manifest.jsonl indexes the currently accepted videos with relative paths. camerarig.json freezes the three camera poses used by the existing set. IDs 000000–000099 are byte-verified independent…

Publicly accessible

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

Dataset

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

[Bui Thu Anh](https://savrn.com/model-publishers/anhbui42938)

Publicly accessible

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

Dataset

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

[Mostafa Behroozi](https://savrn.com/model-publishers/mostafabehroozi)

Publicly accessible

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

Dataset

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

[Amine Harrabi](https://savrn.com/model-publishers/ami1ne)

A curated, clustered video clip dataset built to train a from-scratch, small-parameter (~150-200M) video generation model as part of the Codeically "smallest video gen model" video series. Raw footage (batch01/ … batchNN/) — source videos as collected, each batch with its own manifest.csv: Processed clips (clips/ /.mp4 + clipsmanifest.csv) — the actual training data. Each raw source video is cut into fixed-length windows, resized, and resampled: - 2 seconds per clip, no overlap between windows - ~160px wide (height auto-scaled), landing in a 128–192px band - 10fps (20 frames per clip), landing in an 8–12fps band clipsmanifest.csv columns: clipfilename, cluster, category, source, license…

Publicly accessible other 10K<n<100K

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

Dataset

### [us-federal-public-data-mirror](https://savrn.com/datasets/us-federal-public-data-mirror)

[Reverened Dr Tolerant](https://savrn.com/model-publishers/ai-ministries)

An independent copy of United States federal public datasets that have been removed, discontinued, degraded, or formally proposed for elimination. Everything here was already public and is United States Government work, which is not subject to copyright under Nothing in this mirror is modified. No values are corrected, no records are dropped, no columns are renamed, no formats are converted. Each file is stored exactly as the agency published it, alongside the date it was retrieved and a SHA-256 checksum, so that any copy can be verified against any other copy. This is not affiliated with, endorsed by, or connected to NOAA, the CDC, the EPA, or any other agency or organisation. Two…

Publicly accessible other 1B<n<10B

[View dataset](https://savrn.com/datasets/us-federal-public-data-mirror)

Dataset

### [sn38-sub-gain-19](https://savrn.com/datasets/sn38-sub-gain-19)

[Sunsetcanyon](https://savrn.com/model-publishers/sunsetcanyon)

Publicly accessible

[View dataset](https://savrn.com/datasets/sn38-sub-gain-19)

Dataset

### [sn38-sub-gain-22](https://savrn.com/datasets/sn38-sub-gain-22)

[Sunsetcanyon](https://savrn.com/model-publishers/sunsetcanyon)

Publicly accessible

[View dataset](https://savrn.com/datasets/sn38-sub-gain-22)

## 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.
