# Datasets, Page 49 of 132
Source: https://savrn.com/datasets/page/49
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

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

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

Publicly accessible apache-2.0

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

Dataset

### [r9-work](https://savrn.com/datasets/r9-work)

[DEEPIOS](https://savrn.com/model-publishers/deepios)

Access requested at publisher

[View dataset](https://savrn.com/datasets/r9-work)

Dataset · Other

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

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

prettyname: "Carfax Used Car Listings & Dealer Inventory Dataset" - open-data - data-science - web-scraping - scraper - crawler - data-collection - used-cars - automotive - car-listings - carfax - vehicle-data - dealer-inventory - car-pricing sizecategories: taskcategories: - other - configname: car-listings datafiles: A sample of Carfax marketplace listings with vehicle specs, mileage, dealer ratings, history verification, reliability badges, and One Price value estimates. This dataset is a preview sample of the Carfax 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…

Publicly accessible cc-by-nc-4.0 1M<n<10M

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

Dataset

### [chujian-ocr-shiwen-20260901](https://savrn.com/datasets/chujian-ocr-shiwen-20260901)

[Raphael Wang](https://savrn.com/model-publishers/raphael2099)

本目录是 2026-09-01 正式释文 OCR 的本地交付根目录。 1. 百度 PaddleOCR-VL-1.5 保守首识； 2. Qwen3-VL-4B-Instruct 对照页图和百度结果复核； 3. GPT-5.6 只处理分歧、低置信和版式异常页，不对已一致页做语言润色。 字段分离保存：paddleraw、qwenreview、gptreview、acceptedtext、reviewstatus、sourcesha256。古字图版、无码字和无法解释的分歧必须进入 quarantine，不得静默改成通顺文字。 资产详情、页数、SHA-256 与模型 revision 见 HFASSETMANIFEST20260901.json。

Publicly accessible

[View dataset](https://savrn.com/datasets/chujian-ocr-shiwen-20260901)

Dataset

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

[Le Van Thinh](https://savrn.com/model-publishers/thinhle46721)

Publicly accessible

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

Dataset · Text classification

### [mcp-registry](https://savrn.com/datasets/mcp-registry)

[Vinkius](https://savrn.com/model-publishers/vinkius)

Welcome to the Vinkius Open Data Initiative. We are opening access to the Vinkius connector catalog. This repository provides automatically updated documentation for 10,672 unique connectors for AI agents. This highly structured corpus is designed specifically for AI researchers, data scientists, and language model developers. It provides a robust foundation for advancing artificial intelligence research in the following domains: Extracted programmatically from the Vinkius registry, each record maintains strict structural integrity. The dataset is rigorously indexed with categorical taxonomies, precise tool support configurations, and environmental metadata to ensure a noise-free corpus.…

Publicly accessible cc0-1.0 1K<n<10K

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

Dataset

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

[Kathleen Cole Chen](https://savrn.com/model-publishers/kathleencchen3730)

Publicly accessible

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

Dataset

### [tw-privacy-guides](https://savrn.com/datasets/tw-privacy-guides)

[Twinkle AI](https://savrn.com/model-publishers/twinkle-ai)

門羅幣 (Monero, XMR)： 8AEyT2biCC7S5impodPReHdRrUipEnj3GLFRZStyeUHiWWzq9q8emkpibJiPRxScXranJqKrinEere938k9pWkVcFWYTDzG 比特幣 (Bitcoin, BTC)： bc1qr0h3h9dlhzdu067psskwfsa8c0mfzaryv5626g

Publicly accessible

[View dataset](https://savrn.com/datasets/tw-privacy-guides)

Dataset

### [world_municipal_law](https://savrn.com/datasets/world-municipal-law)

[Benjamin J Barber](https://savrn.com/model-publishers/endomorphosis)

Local (municipal / county / water-board / regional) law worldwide, normalized to one schema. Companion to which stays unchanged. Since 2026-10-11, national, subnational (first-level: state / Land / province / région) and supranational law, i.e. every iso: place (isoFR, isoES-CT, isoEU, …), is published in endomorphosis/worldnationallaw, which uses the same schema and layout. This repo keeps municipal and other local law (municipalities, counties, water boards, …). The iso files were copied there first, verified (sha256 and row counts), and then deleted here in a separate commit; the repo history still has them. - worldlaw/data/{CC}/{placekey}html.parquet: one file per jurisdiction (ZSTD)…

Publicly accessible other

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

Dataset

### [First-nuvaka](https://savrn.com/datasets/first-nuvaka)

[Halil tarık](https://savrn.com/model-publishers/tako121)

Publicly accessible

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

Dataset

### [biomedimageos_repo1](https://savrn.com/datasets/biomedimageos-repo1)

[Ziyanglong](https://savrn.com/model-publishers/zylong)

Access requested at publisher apache-2.0

[View dataset](https://savrn.com/datasets/biomedimageos-repo1)

Dataset

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

[Amber Rae Owens](https://savrn.com/model-publishers/amberrowens2170)

Publicly accessible

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

Dataset

### [Ani4D](https://savrn.com/datasets/ani4d)

[Angel He](https://savrn.com/model-publishers/anhe7)

Ani4D dataset (TBZ + Objaverse + Objaverse-XL, curated 2026-10-04; 16 cameras per clip since 2026-10-04) The curated articulated-character dataset behind Ani4D (PoseAE codec + VoxelFM), plus the 50-asset Ani4D-vs-ActionMesh benchmark under benchmark/. 9,975 kept assets: train 9,791 (TBZ 57 / Objaverse 1,935 / Objaverse-XL 7,799), val 134 (10 / 56 / 68), test = benchmark 50 (8 / 20 / 22); the split is poseaesplit.json at the root and bench50.txt lists the benchmark. Every kept

Publicly accessible other

[View dataset](https://savrn.com/datasets/ani4d)

Dataset · Visual question answering

### [OneStreamer-1M](https://savrn.com/datasets/onestreamer-1m)

[Yuandong Yang](https://savrn.com/model-publishers/yyd7)

Adapted from the paper: task taxonomy on the left; streaming caption and QA construction pipelines on the right. Task coverage A training dataset for perception, memory, and proactive response in streaming video interaction, introduced in OneStreamer: Unifying Perception, Memory, and Proactive Response in Streaming Video Interaction. The curated collections include Streamo, JoyAI-VL-Interaction (JoyVL), MMDuet2, ViSpeak, StreamForest, VideoChat-OL, Seeker, and VST, alongside OneStreamer-Core. The appendix groups upstream sources by collection and task; a source list in the table describes that group rather than assigning every record to all listed sources. Proactive Caption Memory Proactive…

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/onestreamer-1m)

Dataset

### [IndicFairSpeech-private](https://savrn.com/datasets/indicfairspeech-private)

[Anand Rai](https://savrn.com/model-publishers/raianand)

Publicly accessible apache-2.0

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

Dataset

### [naylis_mom_fixed](https://savrn.com/datasets/naylis-mom-fixed)

[Skyline](https://savrn.com/model-publishers/therealskyline)

Publicly accessible

[View dataset](https://savrn.com/datasets/naylis-mom-fixed)

Dataset

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

[Huggingface F1](https://savrn.com/model-publishers/huggingface-f1)

Publicly accessible

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

Dataset

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

[Pham Thu Thanh](https://savrn.com/model-publishers/thanhpham49997)

Publicly accessible

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

Dataset

### [faers_bronze_drug](https://savrn.com/datasets/faers-bronze-drug)

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

Publicly accessible

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

Dataset

### [aizen-journal](https://savrn.com/datasets/aizen-journal)

[Adithya Byri](https://savrn.com/model-publishers/adithyabyri)

Publicly accessible

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

Dataset

### [medical_case_neo4j_graph_db](https://savrn.com/datasets/medical-case-neo4j-graph-db)

[Mohamed Abo El-Enen](https://savrn.com/model-publishers/mohamedahmedae)

Publicly accessible

[View dataset](https://savrn.com/datasets/medical-case-neo4j-graph-db)

Dataset

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

[Yang Zai](https://savrn.com/model-publishers/april-yang)

Access requested at publisher

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

Dataset · Text classification

### [osm-polygon-wikidata-and-wikipedia-landuse](https://savrn.com/datasets/osm-polygon-wikidata-and-wikipedia-landuse)

[Noé Flandre](https://savrn.com/model-publishers/noeflandre)

A land-use / land-cover relevance label for every sentence of NoeFlandre/osm-polygon-wikidata-and-wikipedia (revision d6fc058). The input is mirrored here unchanged; labels and model outputs are separate tables that join back to it. In progress: 100 of 761 input files fully labelled, 661 more partially, 74,791,929 rows, 165 unique texts have their full model outputs published so far (outputs ship with the first complete file that contains the text; labels for the other sentences are in labels/). 928,088 rows (1.2% of all rows) have no Each hexagon is an H3 cell (resolution 3) holding the yes/no sentences whose document's first linked polygon (smallest polygonid with lat/lon) falls in it.…

Publicly accessible odbl

[View dataset](https://savrn.com/datasets/osm-polygon-wikidata-and-wikipedia-landuse)

Dataset

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

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

Publicly accessible

[View dataset](https://savrn.com/datasets/p2-etf-graphon-mean-field-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.