# Datasets, Page 57 of 132
Source: https://savrn.com/datasets/page/57
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

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

[DiscreteRTC Model and Data](https://savrn.com/model-publishers/discretertc)

Publicly accessible

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

Dataset

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

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

Publicly accessible

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

Dataset · Image classification

### [pentimento-core](https://savrn.com/datasets/pentimento-core)

[The Malware Files](https://savrn.com/model-publishers/the-malware-files)

This is a JPEG-decompressed spatial corpus. It is NOT comparable to BOSSbase, whose covers were never JPEG compressed. Detector numbers measured here and numbers measured on BOSSbase cannot be placed in the same table. A steganalysis corpus of 10,000 permissively licensed cover photographs and 344,357 matched stego pairs across 35 arms, where every image carries its own licence and every file carries its own checksum. A further 4 arms hold the 38,119 clean halves those pairs are measured against. Nothing is downloaded until you ask for a sample, so looking costs seconds rather than 48 GB. Each arm is its own config, named exactly as the arm table below names it, and covers is the default.…

Publicly accessible cc-by-4.0 100K<n<1M

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

Dataset

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

[Huynh Ngoc Tuan](https://savrn.com/model-publishers/tuanhuynh39909)

Publicly accessible

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

Dataset

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

[Hannah Hope Ward](https://savrn.com/model-publishers/wardhannah3771)

Publicly accessible

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

Dataset · Image classification

### [neuralatlas-attributions-convnext_tiny](https://savrn.com/datasets/neuralatlas-attributions-convnext-tiny)

[Matías Gómez Carrique](https://savrn.com/model-publishers/matgc04)

Precomputed attribution maps and faithfulness metrics for the torchvision convnexttiny model (default pretrained weights, no fine-tuning) on imagenet-pico, a 3000-image subset of ImageNet-1k with three images for each of the 1000 classes. This repository is part of Neural Atlas, a web tool for comparing attribution methods across vision architectures on the same image, developed as an undergraduate thesis at the Facultad de Informática, Universidad Nacional de La Plata (Argentina). The viewer reads these files directly; they can also be used on their own, without the tool. Methods: CB-RISE, Deconvolution, DeepLift, GradientShap, GuidedBackprop, GuidedGradCam, InputXGradient…

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

[View dataset](https://savrn.com/datasets/neuralatlas-attributions-convnext-tiny)

Dataset

### [exodus-endpoints](https://savrn.com/datasets/exodus-endpoints)

[Sheriff Judes Chandrabose](https://savrn.com/model-publishers/judes1209)

Publicly accessible

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

Dataset

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

[Nu11](https://savrn.com/model-publishers/n0nenu11)

Publicly accessible

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

Dataset

### [mlx-benchmarks](https://savrn.com/datasets/mlx-benchmarks)

[Jacob Evans](https://savrn.com/model-publishers/jacobpevans)

Structured benchmark results for local hardware and hosted-provider language model evaluations. Rows include both local-device runs and provider results; recorded host and accelerator fields may be absent for provider rows. Results are published as immutable Parquet shards by the The default configuration opens data/recent/latest.parquet: the canonical shards published within 30 days of the newest one, newest run first. The publish workflow regenerates it from the canonical shards; it adds no rows of its own. Select history to browse every canonical shard, including older hosted-provider evaluations. Optional result and system fields use nulls when a run did not record them. Historical tag…

Publicly accessible apache-2.0 n<10K

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

Dataset

### [content-202609218d8a](https://savrn.com/datasets/content-202609218d8a)

[Nguyen](https://savrn.com/model-publishers/icdn20)

Publicly accessible

[View dataset](https://savrn.com/datasets/content-202609218d8a)

Dataset

### [grpo_dppo_qwen3_4B_maxrl_polaris1000_knk_rollouts](https://savrn.com/datasets/grpo-dppo-qwen3-4b-maxrl-polaris1000-knk-rollouts)

[Fahim Tajwar](https://savrn.com/model-publishers/ftajwar)

Training rollouts of one verl run, one parquet per trainer step (data/step-.parquet), rows in the order the trainer consumed them; the rollout.n samples of a prompt are contiguous and share uid. prompttokenids / responsetokenids are the exact token ids (special tokens kept, no padding) and rolloutlogprobs the sampling-time log-prob of every response token. input / output are decoded with skipspecialtokens=True and are for reading only. score is the raw reward.

Publicly accessible

[View dataset](https://savrn.com/datasets/grpo-dppo-qwen3-4b-maxrl-polaris1000-knk-rollouts)

Dataset

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

[Vo Hong Cuong](https://savrn.com/model-publishers/cuongvo46647)

Publicly accessible

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

Dataset

### [simplex-edl-checkpoints-public](https://savrn.com/datasets/simplex-edl-checkpoints-public)

[Dmitry Manning-Coe](https://savrn.com/model-publishers/dmanningcoe)

Publicly accessible

[View dataset](https://savrn.com/datasets/simplex-edl-checkpoints-public)

Dataset · Video classification

### [BenchCheck-MetaBenchmark](https://savrn.com/datasets/benchcheck-metabenchmark)

[GMLR](https://savrn.com/model-publishers/gmlrvigil)

840 multiple-choice video questions from 76 public video benchmarks, one item per video, four capability groups x 210 (Perception, Temporal, Spatial / physical, Reasoning / knowledge). The set is the difficulty-first census of the BenchCheck screened pool: items that none of the cheap attackers of the pool screening (text-only, single frame, 32-frame 2B model, options-only, shuffled frames) could solve, ranked by the worst-case attacker percentile, with the marked answers verified against the frames; no cap on any model's accuracy (v6, 2026-09-19: the earlier v5 composition capped the reference model's share of correct answers at 45 %, the cap is dropped so that every row of the leaderboard…

Publicly accessible other n<1K

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

Dataset

### [reflo-audio](https://savrn.com/datasets/reflo-audio)

[Babatunde Adekunle](https://savrn.com/model-publishers/adetunes)

Publicly accessible

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

Dataset

### [L4-GOLD](https://savrn.com/datasets/l4-gold)

[Vase](https://savrn.com/model-publishers/vyckaas)

Publicly accessible

[View dataset](https://savrn.com/datasets/l4-gold)

Dataset

### [aic26-lowres-keyframes](https://savrn.com/datasets/aic26-lowres-keyframes)

[Huynh Nghia](https://savrn.com/model-publishers/htnghiaaa)

Access requested at publisher

[View dataset](https://savrn.com/datasets/aic26-lowres-keyframes)

Dataset

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

[Ly Hai Khoa](https://savrn.com/model-publishers/khoaly38007)

Publicly accessible

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

Dataset

### [immadegen-avatar-outputs](https://savrn.com/datasets/immadegen-avatar-outputs)

[Profile](https://savrn.com/model-publishers/immaverse)

Publicly accessible

[View dataset](https://savrn.com/datasets/immadegen-avatar-outputs)

Dataset

### [12](https://savrn.com/datasets/12)

[Diego Machado](https://savrn.com/model-publishers/store12)

Publicly accessible

[View dataset](https://savrn.com/datasets/12)

Dataset

### [lilm2-eval-artifacts](https://savrn.com/datasets/lilm2-eval-artifacts)

[Akshay Kumar Gautam](https://savrn.com/model-publishers/glouriousgautam)

Publicly accessible

[View dataset](https://savrn.com/datasets/lilm2-eval-artifacts)

Dataset

### [nsa-ka](https://savrn.com/datasets/nsa-ka)

[Victor Quagraine](https://savrn.com/model-publishers/quagrain)

Publicly accessible

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

Dataset · Text classification

### [denner-ch-products](https://savrn.com/datasets/denner-ch-products)

[Yelin Z.](https://savrn.com/model-publishers/yelinz)

All products and their information from Denner Switzerland. The entire catalogue and the current special discounts are all included. Check out similar datasets for other grocery stores - https://huggingface.co/datasets/Yelinz/lidl-ch-products - https://huggingface.co/datasets/Yelinz/migros-ch-products - https://huggingface.co/datasets/Yelinz/coop-ch-products

Publicly accessible cc-by-4.0

[View dataset](https://savrn.com/datasets/denner-ch-products)

Dataset

### [gridrad2020-2022](https://savrn.com/datasets/gridrad2020-2022)

[Qingzhao](https://savrn.com/model-publishers/whyeb4449)

Please use the below bibtex for citation if you use our pre-processed h5 dataset in samples/radarawshdf5v1: Thank you so much.

Publicly accessible mit

[View dataset](https://savrn.com/datasets/gridrad2020-2022)

## 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.
