# Datasets, Page 40 of 132
Source: https://savrn.com/datasets/page/40
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

### [content-2026091710b1](https://savrn.com/datasets/content-2026091710b1)

[Nguyen](https://savrn.com/model-publishers/icdn11)

Publicly accessible

[View dataset](https://savrn.com/datasets/content-2026091710b1)

Dataset · Text retrieval

### [ipfs_iran_laws](https://savrn.com/datasets/ipfs-iran-laws)

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

Research snapshot of official legislation collected from DOTIC dotic.ir. Not legal advice. Official gazettes / government portals prevail over this corpus. - data/laws.parquet — one row per instrument (id, title, full text, dates, status, identifiers, article count, source URL). - data/articles.parquet — one row per article/section (lawid, article number, title, text, source URL). - scrapers/collectir.py — research collector used to build this snapshot. - scrapers/common.py — shared collector helpers. - scrapers/worldlib.py — shared fetch (live official URL, Wayback fallback). - scrapers/archivefallbacks.py — Wayback / Common Crawl CDX helpers. Official government / gazette texts; reuse per…

Publicly accessible other 1K<n<10K

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

Dataset

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

[A Smol Course](https://savrn.com/model-publishers/smol-course)

Publicly accessible

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

Dataset

### [ai-shorts-videos](https://savrn.com/datasets/ai-shorts-videos)

[Yuji Mo](https://savrn.com/model-publishers/ymo2017)

Publicly accessible

[View dataset](https://savrn.com/datasets/ai-shorts-videos)

Dataset

### [arc-voicesamples-generated](https://savrn.com/datasets/arc-voicesamples-generated)

[Goea](https://savrn.com/model-publishers/goea)

Publicly accessible

[View dataset](https://savrn.com/datasets/arc-voicesamples-generated)

Dataset

### [course-certificates-of-excellence](https://savrn.com/datasets/course-certificates-of-excellence)

[Hugging Face Agents Course](https://savrn.com/model-publishers/agents-course)

Publicly accessible

[View dataset](https://savrn.com/datasets/course-certificates-of-excellence)

Dataset

### [octopus-eternal](https://savrn.com/datasets/octopus-eternal)

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

Publicly accessible

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

Dataset

### [historical-danbooru-tag-counts](https://savrn.com/datasets/historical-danbooru-tag-counts)

[John Steward](https://savrn.com/model-publishers/hdiffusion)

Publicly accessible apache-2.0

[View dataset](https://savrn.com/datasets/historical-danbooru-tag-counts)

Dataset

### [dataset1](https://savrn.com/datasets/dataset1)

[Zakaria Nasrul Jabbar](https://savrn.com/model-publishers/zackyy23)

Publicly accessible mit

[View dataset](https://savrn.com/datasets/dataset1)

Dataset

### [ailab_fyy](https://savrn.com/datasets/ailab-fyy)

[Yapeng Mi](https://savrn.com/model-publishers/mickeymouse2024)

Publicly accessible

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

Dataset

### [ballard-observatory](https://savrn.com/datasets/ballard-observatory)

[Kenny Olufowobi](https://savrn.com/model-publishers/x1489)

Every public record and measurement about the Ballard neighborhood of Seattle that the Ballard Observatory platform collects, in one open, queryable lake. It is refreshed automatically. Raw values are stored as strings exactly as published (objects as JSON), so upstream schema changes never lose data. Typed SQL views, including a unified events view, are defined in platform/bo/views.py. Only public records are collected. Personal fields are removed at ingest: - liquor-license applicants' names, birthdates and phone numbers - sole proprietors' legal names and business phone numbers Locations that publishers redact (for example SPD's redacted locations) stay redacted. Personal fields removed…

Publicly accessible other 1M<n<10M

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

Dataset · Other

### [AnyHand-Dataset](https://savrn.com/datasets/anyhand-dataset)

[Chen Si](https://savrn.com/model-publishers/chen-si-02)

Original AnyHand standard TAR shards for synthetic hand-pose research. This is a distribution mirror of the Harvard Dataverse source, persistent ID doi:10.7910/DVN/VBYEK3, source version:draft. Transfer in progress or partial. Uploaded samples: 4,868,096. Failed items are excluded, not replaced with partial shards. Check transfersummary.json before treating this mirror as a complete release. Each published TAR contains exactly 1024 samples. Every sample's RGB, depth, and annotation were decoded and checked locally; PNG checksums and TAR end markers were checked. Optional masks were checked when present. Upload size and SHA-256 were confirmed through HF metadata. Files preserve source split…

Access requested at publisher cc-by-nc-nd-4.0

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

Dataset

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

[Boread](https://savrn.com/model-publishers/boreaddataset)

Boread A Dataset and Benchmark for Dynamic UAV Viewpoint Scheduling in Aerial-Ground Cooperative Perception Hugging Face dataset · Anonymous code is a CARLA-Air-based dataset and benchmark for active viewpoint selection in aerial-ground cooperative perception. A UAV selects successive viewpoints to reveal targets occluded

Publicly accessible

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

Dataset · Other

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

[Andrej Leban](https://savrn.com/model-publishers/andleb)

CausalDS is a benchmark generator for causal reasoning in data-science agents. Each generated scene pairs a synthetic structural causal model with tabular data and an audited natural-language story. Tasks span association, intervention, and counterfactual reasoning, including estimation, uncertainty, causal structure, and knowing when to abstain. This release contains the 100-task realistic exam and the observation-layer and CauseNet-seeding ablations, including evaluation inputs, reference answers, and held-out test labels. The code repository provides the generator, agent harness, and deterministic grader. The CausalDSScore $\times$ $\log$ tokens per task plane separates the latest closed…

Publicly accessible cc0-1.0

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

Dataset · Text retrieval

### [ipfs_malawi_laws](https://savrn.com/datasets/ipfs-malawi-laws)

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

Research snapshot of official legislation collected from MalawiLII / Parliament of Malawi. Not legal advice. Official gazettes / government portals prevail over this corpus. - data/laws.parquet — one row per instrument (id, title, full text, dates, status, identifiers, article count, source URL). - data/articles.parquet — one row per article/section (lawid, article number, title, text, source URL). - scrapers/collectmw.py — research collector used to build this snapshot. - scrapers/common.py — shared collector helpers. - scrapers/worldlib.py — shared fetch (live official URL, Wayback fallback). - scrapers/archivefallbacks.py — Wayback / Common Crawl CDX helpers. Official government /…

Publicly accessible other 1K<n<10K

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

Dataset

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

[Luis](https://savrn.com/model-publishers/luisluis123)

Publicly accessible

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

Dataset

### [img-storage-01](https://savrn.com/datasets/img-storage-01-4)

[Nguye](https://savrn.com/model-publishers/ibkcdn2)

Publicly accessible

[View dataset](https://savrn.com/datasets/img-storage-01-4)

Dataset · Speech recognition

### [dialectal-arabic-voices](https://savrn.com/datasets/dialectal-arabic-voices)

[Moaead](https://savrn.com/model-publishers/moaead)

An expanding collection of Arabic audio from YouTube, SoundCloud, and other sources. Currently labelled Palestinian Arabic (ps). 53,194 recordings · approximately 9,573.3 hours · 501.14 GB Audio retains its original format and sample rate. Recordings have not yet been segmented or individually checked for dialect. New audio is added in ~5 GB Parquet files. The final incomplete file is held locally until it fills.

Publicly accessible

[View dataset](https://savrn.com/datasets/dialectal-arabic-voices)

Dataset · Speech recognition

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

[Kapture CX](https://savrn.com/model-publishers/kapturecx)

Dual-channel synthetic Indian customer-support calls for training full-duplex speech-to-speech models. 81,152 calls · 1,880.2 hours · 2201 shards (last updated 2026-10-05 09:06 IST) Each row's audio is a stereo FLAC at 24000 Hz: Hindi is written in Devanagari, English in Latin, in the same string — "आपका order अभी out for delivery है". Romanized Hindi is rejected by a QA gate. Everything the TTS spoke is spelled out: no digits (₹4,500 → चार हज़ार पाँच सौ रुपये), abbreviations letter-by-letter in Devanagari (OTP → ओ टी पी), phone numbers in two-digit batches (अट्ठानवे चालीस पैंतालीस बावन तिरासी). Backchannels are deliberately Latin (ji, hmm ji, haan ji). - callid, audio, durations…

Access requested at publisher cc-by-nc-4.0

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

Dataset

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

[Kpinquan](https://savrn.com/model-publishers/kpinquan)

Publicly accessible

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

Dataset

### [Video_log](https://savrn.com/datasets/video-log)

[Marvelic](https://savrn.com/model-publishers/topgunm)

Publicly accessible

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

Dataset

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

[Fabricio Da Silva](https://savrn.com/model-publishers/fabricioslv)

Dataset privado de pesquisa para o projeto Mars Monoculture Sovereign OS (OmniMind). - Simulação da monocultura (Spirulina → batata → trigo) com dados reais de Marte - Histerese operacional, metaestabilidade, Dodecatíade agrícola (12 setores) Cada arquivo mantém a estrutura original do PDS. Os manifestos registram dataset/file/ok. - Triad pública compilada no Colab: kernelcompute (Ma'at), freud10d (INRC), sovereignkuramoto (Kuramoto + Hopf) - parquet/: dados vetorizados em parquet zstd (REMS 1521 sols com D12/D13/D15; MOLA tiles; SEIS eventos) - simulations/: kernel emulado × máquina marciana — 300 sols com Φ/Ψ/σ/ε, Ma'at, Rpair (kuramoto 12 casas), regime Hopf - Reconhecimento Dodecatíade…

Publicly accessible other

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

Dataset

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

[Nguyen Quang Huy](https://savrn.com/model-publishers/33bit)

Publicly accessible

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

Dataset

### [Niji_1_Handsome-meta](https://savrn.com/datasets/niji-1-handsome-meta)

[D16](https://savrn.com/model-publishers/dsixteen)

Publicly accessible

[View dataset](https://savrn.com/datasets/niji-1-handsome-meta)

## 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.