# Datasets, Page 45 of 132 Source: https://savrn.com/datasets/page/45 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 ### [usa-2026-midterms-divergence](https://savrn.com/datasets/usa-2026-midterms-divergence) [AFOS Analytics](https://savrn.com/model-publishers/afos-analytics1) What the market priced and what the polls measured about the same election, day by day, before it happened. - 419 national generic-ballot polls from 71 pollsters, fieldwork 2025-04-19 → 2026-09-17, 417 of them with the institute's own source URL - 23784 market price rows across 9 Polymarket contracts: chamber control, seat distributions, turnout, popular-vote margin, and whether the election happens on schedule - 517 headlines from 52 daily collections over a fixed list of 23 outlets - One already decided race with its verified outcome: the Texas Republican Senate primary runoff The Texas Senate Republican runoff resolved on May 26, 2026. Ken Paxton beat John Cornyn with 63.8% of more than… Publicly accessible cc-by-4.0 [View dataset](https://savrn.com/datasets/usa-2026-midterms-divergence) Dataset ### [master-thesis-method2-pat](https://savrn.com/datasets/master-thesis-method2-pat) [Mania](https://savrn.com/model-publishers/mania-bioinformatics) Access requested at publisher [View dataset](https://savrn.com/datasets/master-thesis-method2-pat) Dataset ### [PANEL_IMAGES](https://savrn.com/datasets/panel-images) [M. Sameer](https://savrn.com/model-publishers/sameer958) Publicly accessible [View dataset](https://savrn.com/datasets/panel-images) Dataset ### [co_video_1](https://savrn.com/datasets/co-video-1) [Raymondt](https://savrn.com/model-publishers/raymondt) Publicly accessible [View dataset](https://savrn.com/datasets/co-video-1) Dataset · Text classification ### [ai-detector-data](https://savrn.com/datasets/ai-detector-data) [Adaptive Classifier](https://savrn.com/model-publishers/adaptive-classifier) A continuously-growing collection of AI text detection predictions with optional user feedback, generated from the AI Text Detector Space. Every time someone analyzes text or a URL on the Space, the prediction is appended to this dataset. Users can also click "Correct" or "Incorrect" to provide feedback, which gets stored alongside the prediction. Or with the datasets library: 1. Model evaluation — see how the detector performs on real-world text submitted by users 2. Retraining data — records with feedback provide ground-truth labels for continuous learning 3. Failure analysis — examine where the model is wrong (feedback == "incorrect") 4. Distribution analysis — what kinds of text/URLs… Publicly accessible apache-2.0 n<1K [View dataset](https://savrn.com/datasets/ai-detector-data) Dataset ### [4tb](https://savrn.com/datasets/4tb) [ZIJING XU](https://savrn.com/model-publishers/annyorange) Publicly accessible [View dataset](https://savrn.com/datasets/4tb) Dataset ### [Niji_1_Woman-control](https://savrn.com/datasets/niji-1-woman-control) [D16](https://savrn.com/model-publishers/dsixteen) Publicly accessible [View dataset](https://savrn.com/datasets/niji-1-woman-control) Dataset ### [ipfs_spain_municipal_laws](https://savrn.com/datasets/ipfs-spain-municipal-laws) [Benjamin J Barber](https://savrn.com/model-publishers/endomorphosis) Pack 1 holds recent announcements from the Butlletí Oficial de la Província de Barcelona (bop.diba.cat), published by the Diputació de Barcelona. Each row is one anuncio with its full text extracted from the official PDF. Other provincial bulletins may join later packs. Private webmail addresses (gmail, hotmail, outlook, live, yahoo, icloud, aol, proton, gmx, yandex, telefonica.net, terra.es and similar; full list in scrapers/esboplib.py, WEBMAILDOMAINS) are replaced with [email redacted] in law titles and texts, and so in article texts. Council, Diputació and other institutional addresses (.cat,.es,.gov, council domains) are kept as published. The redaction is a deterministic pack step… Publicly accessible other [View dataset](https://savrn.com/datasets/ipfs-spain-municipal-laws) Dataset ### [ramanv-stt-filtered](https://savrn.com/datasets/ramanv-stt-filtered) [Some](https://savrn.com/model-publishers/guruawe) Access requested at publisher [View dataset](https://savrn.com/datasets/ramanv-stt-filtered) Dataset · Other ### [siriusxm-dataset](https://savrn.com/datasets/siriusxm-dataset) [Rebrowser.net](https://savrn.com/model-publishers/rebrowser) prettyname: "SiriusXM Channels & Airplay Dataset" - siriusxm - satellite-radio - radio - airplay - music-data - open-data - data-science - web-scraping - scraper - crawler - data-collection sizecategories: taskcategories: - other - configname: channels datafiles: - configname: channel-plays datafiles: Satellite radio channel lineup with genres, categories, channel numbers across platforms, and real-time play-by-play track history across SiriusXM music channels. The SiriusXM dataset on Rebrowser is free — but HuggingFace has file size limits, so this dataset contains a limited sample. For the full dataset (63.7M records, updated daily), visit rebrowser.net/products/datasets/siriusxm. This… Publicly accessible cc-by-nc-4.0 10M=4, correctness>=3, naturalness>=3). Companion repos hold quality-gate rejects (rejected-) and records whose judge call failed (unjudged-). Publicly accessible [View dataset](https://savrn.com/datasets/nepali-law-v2) Dataset · Text generation ### [rejected-nepali-law-v2](https://savrn.com/datasets/rejected-nepali-law-v2) [Aaraj Bhatar](https://savrn.com/model-publishers/aarajbhattarai) Synthetic Nepali instruction-tuning data generated with NVIDIA NeMo Data Designer from authoritative Nepali documents (agriculture manuals, legal texts). Answers are grounded strictly in the source; unanswerable questions get an explicit refusal. Records use chat messages format plus metadata and per-record qualityscores (grounding / correctness / naturalness, 1-5, LLM-as-judge). One data/train-.jsonl per source document; shards are overwritten idempotently on re-runs. Records judged BELOW the quality gate; each has rejectreasons. Useful for judge calibration, hard-negative mining, or re-filtering with different thresholds. Do NOT use as-is for instruction tuning. Publicly accessible [View dataset](https://savrn.com/datasets/rejected-nepali-law-v2) Dataset · Image to image ### [tintedglass-rdt-synth](https://savrn.com/datasets/tintedglass-rdt-synth) [Zmy1234567890](https://savrn.com/model-publishers/zmy1234567890) SIRR 合成集（一般 p=1）的关键差别。 合成测试集目录：gt/t{XX}.png（透射 GT）、r/t{XX}.png（反射层）、 levels/alpha{lv}/t{XX}.png（各档输入）、alpha/（透过率场）、meta.json。 注意：无反射参考帧（T.png / GT.png）与 vehiclessd 训练数据字节级同源， DONOTUSEINTRAINING.md）。 这条数据用于 RDNet（CVPR 2025）的贴膜域微调：冻 FocalNet 主干训练其余参数， 配套权重见 zmy1234567890/tintedglass-rdnet-synth-ft。 重要负结果：合成域微调不能迁移到实拍（三套实拍配对集 gain-matched PSNR 全部变差 −0.44 ~ −3.87 dB，Wilcoxon p<0.05）。候选原因是合成 T 无噪声/JPEG、 - 合成层（T 源、R 池）来自公开学术数据集（SIR²、RRWDataset 等），仅供研究； Publicly accessible other [View dataset](https://savrn.com/datasets/tintedglass-rdt-synth) Dataset · Tabular regression ### [weather_forecast_japan](https://savrn.com/datasets/weather-forecast-japan) [Junichiro Niimi](https://savrn.com/model-publishers/jniimi) This dataset contains daily-collected weather forecasts for up to seven days ahead for all the meteorological observatories in Japan, published by the Japan Meteorological Agency (JMA) at https://www.jma.go.jp/bosai/forecast/. We collect, structurize, and accumulate the prediction since the page is overridden whenever the information is updated. The data is automatically updated daily using GitHub Actions. Since the actual forecasts are published multiple times a day, we set up the column fromhour which represetnts the announced time. Further details are also available at note.com/jniimi/n/n06d3423bbbbf (Japanese only). This dataset can be utilized across a wide range of research fields.… Publicly accessible cc-by-4.0 10K