# Datasets, Page 42 of 132
Source: https://savrn.com/datasets/page/42
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

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

[Hoang Trung Nguyen](https://savrn.com/model-publishers/hoangtrungnguyen)

Publicly accessible

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

Dataset

### [financial-lakehouse](https://savrn.com/datasets/financial-lakehouse)

[Yoshimasa_Daiya](https://savrn.com/model-publishers/yoshi-dai)

NOTICE: DO NOT USE THIS DATASET FOR ANY COMMERCIAL OR AI TRAINING PURPOSES. UNAUTHORIZED REDISTRIBUTION IS STRICTLY PROHIBITED. 本データセットは、金融庁のEDINETが公開しているXBRLデータを著作者が独自に解析・蓄積したものです。 - 本データセットは Gated Dataset です。 - データの取得を希望する場合は、Hugging Faceアカウントでログインし、アクセスリクエストを行ってください。 - 2026年5月2日：ライセンスをMITから独自規約に変更し、アクセス制限（Gated/Manual Approval）を導入しました。

Publicly accessible other

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

Dataset

### [wham3d-cts-trace-markov-rollouts-20260923](https://savrn.com/datasets/wham3d-cts-trace-markov-rollouts-20260923)

[Robert Osazuwa Ness](https://savrn.com/model-publishers/osazuwa)

Growing, publicly downloadable video-backed rollout dataset for the tracemarkov ablation arm at training step 500, seed 20260921. Each selected frozen observational prefix has exactly one cached continuation in each of two routes: null-intervention observational and diagnostic do(X=1). Prefix IDs are sorted once within each (W,Z) stratum and remain balanced as the cohort grows. The direct route of an observationally trained arm is a diagnostic; it does not replace the paper's observational importance-weighted estimator. Sampling note. Rollouts use a growing key-value cache: every generated frame attends to the whole history since the prefix, up to 280 frames, at absolute temporal positions.…

Publicly accessible

[View dataset](https://savrn.com/datasets/wham3d-cts-trace-markov-rollouts-20260923)

Dataset

### [blob-rsw-0923](https://savrn.com/datasets/blob-rsw-0923)

[Wei Pang](https://savrn.com/model-publishers/weipang142857)

Access requested at publisher

[View dataset](https://savrn.com/datasets/blob-rsw-0923)

Dataset

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

[Lev Kremlev](https://savrn.com/model-publishers/levkremlev888)

Publicly accessible

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

Dataset

### [content-2026091905b5](https://savrn.com/datasets/content-2026091905b5)

[Byte I](https://savrn.com/model-publishers/icdn15)

Publicly accessible

[View dataset](https://savrn.com/datasets/content-2026091905b5)

Dataset

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

[Do Tuan Minh](https://savrn.com/model-publishers/benxelua)

Publicly accessible

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

Dataset

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

[Ho Hai Khanh](https://savrn.com/model-publishers/khanhho13537)

Publicly accessible

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

Dataset

### [p2-etf-anp-results](https://savrn.com/datasets/p2-etf-anp-results)

[Pranab Pattanaik](https://savrn.com/model-publishers/p2samapa)

Publicly accessible

[View dataset](https://savrn.com/datasets/p2-etf-anp-results)

Dataset

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

[Haochang Hao](https://savrn.com/model-publishers/liofoil)

This repository is a private migration archive, not a public dataset release or a single uniform loaddataset table. Companion code, detailed recovery manual and sanitized research/conversation history: Start with GitHub RESTORE.md, CODEXHANDOFF.md, and docs/RESEARCHHISTORY.md. Download only the explicit files in migration/artifactsmanifest.json, using the frozen HF commit recorded in the companion GitHub migration/artifactrelease.json. Contents: eight consecutive open research stages, base examples, lifetime fitting, calibration, generated controlled edits, split manifests, predictions, training checkpoints, all failed attempts/configuration logs, API usage estimates, tables and reports…

Publicly accessible

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

Dataset · Other

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

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

prettyname: "SeatGeek Events & Ticket Listings Dataset" - open-data - data-science - web-scraping - scraper - crawler - data-collection - tickets - seatgeek - events - concerts - sports - ticket-prices - deal-score sizecategories: taskcategories: - other - configname: events datafiles: - configname: event-listings datafiles: - configname: performers datafiles: - configname: venues datafiles: Daily sample of SeatGeek events, ticket listings, performers, and venues with Deal Score ratings, section-level seating, delivery types, and cross-platform IDs. This dataset is a preview sample of the SeatGeek dataset published by Rebrowser. If you're doing academic research, you may be eligible for…

Publicly accessible cc-by-nc-4.0 100M<n<1B

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

Dataset

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

[Michael Wayne Brooks](https://savrn.com/model-publishers/michaelwbrooks2399)

Publicly accessible

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

Dataset

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

[Bui Bao Linh](https://savrn.com/model-publishers/linhbui35795)

Publicly accessible

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

Dataset

### [ua-entity-graph](https://savrn.com/datasets/ua-entity-graph)

[Jo Talbot](https://savrn.com/model-publishers/jotalbot)

Сборка: 2026-10-14 03:40 UTC Файл links.db — SQLite: таблицы entities, mentions, edges. Запросы: python scripts/entitylinks.py search --db links.db --id. Источники: ЄДР, ПДВ, ЄДРСР, а також person-реестры (wanted, missing, notaries, courtexperts, arbitrationmanagers, advocates, auditors, debtors). Точная входная provenance: graphprovenance.json содержит URL, локальный путь, размер и SHA-256 каждого успешно скачанного файла. Рёбра identity/nameresolve — консервативное разрешение по ФИО. обезличивание источника сохраняется (nodeanonymization).

Publicly accessible

[View dataset](https://savrn.com/datasets/ua-entity-graph)

Dataset

### [website_crawl_0924](https://savrn.com/datasets/website-crawl-0924)

[Li Li](https://savrn.com/model-publishers/l1997i)

Pages and images of 61 catalog websites (40 topic categories), collected live from the sites' public origins. Candidate URLs are the sites' complete Common Crawl URL inventories (all 128 collections, legacy indexall selection) plus links discovered on saved pages. raw/.origin.html.gz — the HTML exactly as served (gzip). pages/.html.gz — a passive, cleaned HTML rendition (no scripts, styles or forms; ordered media), with the page's images localized once they were downloaded. documents/.json.gz — the manifest: URL, capture time, HTTP metadata, provenance (Common Crawl record or discovering page), quality label, title, ordered media list with each image's local path and SHA-256. Images are…

Access requested at publisher other

[View dataset](https://savrn.com/datasets/website-crawl-0924)

Dataset

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

[Rss Kb](https://savrn.com/model-publishers/fkvoo)

Access requested at publisher

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

Dataset

### [call-center-prod-data](https://savrn.com/datasets/call-center-prod-data)

[Mark muller](https://savrn.com/model-publishers/markmuller)

Access requested at publisher

[View dataset](https://savrn.com/datasets/call-center-prod-data)

Dataset

### [viet_co_video_3](https://savrn.com/datasets/viet-co-video-3)

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

Publicly accessible

[View dataset](https://savrn.com/datasets/viet-co-video-3)

Dataset

### [loki-expLLM](https://savrn.com/datasets/loki-expllm)

[squad (FR)](https://savrn.com/model-publishers/squad-rnd)

This dataset contains interaction logs from the Loki project, a research initiative focused on creating scalable, LLM-powered honeypots. The data captures requests made to three different honeypot experiments (Exp0, Exp1, and Exp2), each with a unique architecture and purpose. The primary goal of this dataset is to provide researchers and security professionals with real-world examples of interactions with different honeypot strategies. The interactions include legitimate-looking traffic, automated scanning, and various exploitation attempts such as SQL Injection (SQLi), Cross-Site Scripting (XSS), Remote Code Execution (RCE), and fuzzing. This dataset can be used for a variety of tasks in…

Publicly accessible cc-by-nc-4.0

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

Dataset

### [9router-data](https://savrn.com/datasets/9router-data-3)

[Bertand](https://savrn.com/model-publishers/bertandd)

Publicly accessible

[View dataset](https://savrn.com/datasets/9router-data-3)

Dataset

### [komorebi-painter-teachers](https://savrn.com/datasets/komorebi-painter-teachers)

[Chinmay Harshavardhan Karkar](https://savrn.com/model-publishers/ck0607)

This dataset stores the 40 fixed COCO128 reference JPEGs used by the painter teacher benchmark. The source metadata and per-image provenance are in refs.json; SHA-256 hashes are in reference-manifest.json. The source records do not establish per-image licensing, so this dataset card does not assert a blanket image license. Generated benchmark results will be uploaded under runs/ with their own manifests after each run.

Publicly accessible

[View dataset](https://savrn.com/datasets/komorebi-painter-teachers)

Dataset

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

[Latency Sensitive Bench](https://savrn.com/model-publishers/latency-sensitive-bench)

Publicly accessible

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

Dataset

### [HF004](https://savrn.com/datasets/hf004)

[Nikodem Levy](https://savrn.com/model-publishers/hf004)

Publicly accessible

[View dataset](https://savrn.com/datasets/hf004)

Dataset

### [engageai-regression-results](https://savrn.com/datasets/engageai-regression-results)

[Madhukar Govindaraju](https://savrn.com/model-publishers/numly)

Publicly accessible

[View dataset](https://savrn.com/datasets/engageai-regression-results)

## 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.
