# Datasets, Page 118 of 132 Source: https://savrn.com/datasets/page/118 Markdown alternate of the page above; the site index is https://savrn.com/llms.txt --- 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 - [10K1T16](https://savrn.com/datasets?size=n%3E1T) - [1B1M1](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 ### [lp2b](https://savrn.com/datasets/lp2b) [Bangkalan](https://savrn.com/model-publishers/pupr) Publicly accessible [View dataset](https://savrn.com/datasets/lp2b) Dataset ### [ltown-leak-scenarios](https://savrn.com/datasets/ltown-leak-scenarios) [Helain ZIMMERMANN](https://savrn.com/model-publishers/helain) Publicly accessible [View dataset](https://savrn.com/datasets/ltown-leak-scenarios) Dataset ### [lua-agent-evals](https://savrn.com/datasets/lua-agent-evals) [Jeorge A.](https://savrn.com/model-publishers/jeorgexyz) The evidence behind lua-agent-lab, from lua-agent. The experiment separates structural tool-call validity from useful tool selection and complete task success. The test split is an inspectable demonstration suite, not a training set or a representative benchmark. Do not treat 30 trials as 30 independent problems: ten prompts are repeated with 0, 1 and 2 trailing spaces, matching the original ablation. No confidence interval or population-level claim is implied. Generated with python -m space.exportdataset --tiny --qwen from the source repository. Each measured row includes its UTC collection time, a SHA-256 digest of the relevant source, exact settings and pinned model revisions.… Publicly accessible mit n<1K [View dataset](https://savrn.com/datasets/lua-agent-evals) Dataset ### [m2mdataset](https://savrn.com/datasets/m2mdataset) [Weibang Han](https://savrn.com/model-publishers/whop3) Publicly accessible [View dataset](https://savrn.com/datasets/m2mdataset) Dataset ### [maize_seedling_msdd_detection](https://savrn.com/datasets/maize-seedling-msdd-detection) [AgML](https://savrn.com/model-publishers/project-agml) Publicly accessible [View dataset](https://savrn.com/datasets/maize-seedling-msdd-detection) Dataset · Image to image ### [manga-colorization-painted](https://savrn.com/datasets/manga-colorization-painted) [Yama Warrior](https://savrn.com/model-publishers/yama2077) Each row is one manga panel: the original black-and-white panel (bw) and one painted full-color version (colored), generated by Qwen-Image 2.1 Turbo with one fixed prompt (no tags, no variants). The paint covers the ink, with strong lighting and shading, while characters and scene stay as drawn. Columns: bw, colored (images), panel (path in the source), source (A = file repo, B = parquet repo), series, chapter, and four quality numbers: grayssim (line art survived), meanchroma (colorfulness), blacklit (solid black that came out bright), whitedark (empty paper that came out dark). No quality filtering has been applied. Copyright and content: the source panels belong to their respective… Access requested at publisher other [View dataset](https://savrn.com/datasets/manga-colorization-painted) Dataset ### [marinskyrl-opd-mopd-repro-artifacts](https://savrn.com/datasets/marinskyrl-opd-mopd-repro-artifacts) [Open Athena](https://savrn.com/model-publishers/open-athena) This public dataset repository preserves the September 2026 MarinSkyRL OPD/MOPD experiment artifacts. artifacts-complete.tar.zst contains the entire original artifacts/ directory, including source checkouts, their Git metadata, the nested local development environment, data, logs, manifests, reports, and symlinks. SHA-256: efcc781203003f67274e23f05e19c6b47679bd761718517ec6241a0e8b0a0b71. The browsable files below are a release copy of the report and evidence directories with links changed to public URLs; the archive preserves the original bytes. To extract the complete tree: zstd -dc artifacts-complete.tar.zst | tar -xf -. The nested.venv is an archival record of the local environment, not… Publicly accessible [View dataset](https://savrn.com/datasets/marinskyrl-opd-mopd-repro-artifacts) Dataset ### [mass-flood-watch-tiles](https://savrn.com/datasets/mass-flood-watch-tiles) [Mohabeldokla](https://savrn.com/model-publishers/mohabeldokla) Publicly accessible [View dataset](https://savrn.com/datasets/mass-flood-watch-tiles) Dataset · Image segmentation ### [massachusetts-roads](https://savrn.com/datasets/massachusetts-roads) [Lam Tran](https://savrn.com/model-publishers/lammtfkday) High-resolution aerial imagery benchmark for remote sensing road extraction, based on the canonical Massachusetts Roads dataset introduced by Volodymyr Mnih (2013). The Massachusetts Roads Dataset covers diverse urban, suburban, coastal, and forested rural environments throughout the Commonwealth of Massachusetts. Standard benchmark partition for road extraction research: If you use this dataset in your research, please cite Publicly accessible mit n<1K [View dataset](https://savrn.com/datasets/massachusetts-roads) Dataset · Text to speech ### [matcha-tts-multilingual-datasets](https://savrn.com/datasets/matcha-tts-multilingual-datasets) [Ha Vu](https://savrn.com/model-publishers/cong123779) Kho dữ liệu âm thanh đa ngôn ngữ (Tiếng Việt & Tiếng Anh) chuẩn phòng thu SOTA, được tiền xử lý và thẩm định toàn diện (SQUIM noise assessment, trích xuất vector âm sắc ECAPA-TDNN 192-d, căn chỉnh phụ đề JSON/timestamps, Mel-spectrogram & F0 pitch contours) phục vụ tối ưu cho việc huấn luyện và suy luận mô hình Matcha-TTS kết hợp Vocoder Vocos. Toàn bộ dữ liệu âm thanh lớn được đóng gói thành các Shard tiêu chuẩn 2.5 GB – 3.0 GB (.tar.gz) để tối ưu hoá băng thông, tránh lỗi timeout và tương thích hoàn hảo với giới hạn Git LFS của Hugging Face. Số lượng: 36 vector đặc trưng âm sắc cho tất cả các giọng nói. Định dạng:.npy (NumPy Array), Shape (192,), Dtype float32, chuẩn hoá $L2$-norm = 1.0.… Publicly accessible apache-2.0 100K