# Datasets, Page 108 of 136 Source: https://savrn.com/datasets/page/108 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. 11,442Models 3,247Datasets 285Papers 6,976Publishers 12,091Sourced relationships Updated 2026-10-19 · [How the library is built](https://savrn.com/model-hub/methodology) ## Filter Datasets Task - [Text generation127](https://savrn.com/datasets?task=Text+generation) - [Robotics108](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 answering38](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 text20](https://savrn.com/datasets?task=Image+to+text) - [Image classification16](https://savrn.com/datasets?task=Image+classification) - [Visual question answering15](https://savrn.com/datasets?task=Visual+question+answering) - [Object detection14](https://savrn.com/datasets?task=Object+detection) - [Text to speech14](https://savrn.com/datasets?task=Text+to+speech) - [Image to image13](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) - [Feature extraction8](https://savrn.com/datasets?task=Feature+extraction) - [Audio classification7](https://savrn.com/datasets?task=Audio+classification) - [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 - [other268](https://savrn.com/datasets?license=other) - [apache-2.0238](https://savrn.com/datasets?license=apache-2.0) - [mit237](https://savrn.com/datasets?license=mit) - [cc-by-4.0232](https://savrn.com/datasets?license=cc-by-4.0) - [cc-by-nc-4.078](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-4.021](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-nc-sa-3.02](https://savrn.com/datasets?license=cc-by-nc-sa-3.0) - [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) Access - [Publicly accessible2,994](https://savrn.com/datasets?access=open_access) - [Access requested at publisher253](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 Xie24](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) - [Sota11](https://savrn.com/datasets?publisher=sotaagi2030) - [Ai210](https://savrn.com/datasets?publisher=allenai) - [Ps Yo10](https://savrn.com/datasets?publisher=atokforps) - [Dougall DeepMind10](https://savrn.com/datasets?publisher=dougalldeepmind) - [D1610](https://savrn.com/datasets?publisher=dsixteen) - [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) Size - [10K1T16](https://savrn.com/datasets?size=n%3E1T) - [1B1M1](https://savrn.com/datasets?size=n%3E1M) Domain - [LeRobot32](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) - [robotics, bimanual-manipulation, imitation-learning4](https://savrn.com/datasets?domain=robotics%2C+bimanual-manipulation%2C+imitation-learning) - [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) - [land-records, deeds, ocr3](https://savrn.com/datasets?domain=land-records%2C+deeds%2C+ocr) - [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) [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) 3,247 datasets, sorted by most downloaded. Dataset ### [adrenal-pseudolabels](https://savrn.com/datasets/adrenal-pseudolabels) [Higazy](https://savrn.com/model-publishers/ahigazy1) Publicly accessible [View dataset](https://savrn.com/datasets/adrenal-pseudolabels) Dataset ### [ae4753ac815876eb8cb66e5c003f337bb3093242](https://savrn.com/datasets/ae4753ac815876eb8cb66e5c003f337bb3093242) [Chang Yu](https://savrn.com/model-publishers/g1n0st) Publicly accessible [View dataset](https://savrn.com/datasets/ae4753ac815876eb8cb66e5c003f337bb3093242) Dataset · Text generation ### [aegis-persona-sovereign-node](https://savrn.com/datasets/aegis-persona-sovereign-node) [Abdullah Ashraf](https://savrn.com/model-publishers/abdullahashraf122) The Aegis Sovereign Node Persona & Technical Dialogue Dataset is an augmented ChatML instruction-tuning dataset designed to condition autonomous agents with the visionary, commanding, and authoritative cadence of an elite technology founder while rigorously defending complex engineering architecture. The dataset pairs high-intensity investor/architectural queries against the Aegis Sovereign Node, balancing macro-strategic vision (inspired by legendary product keynotes) with micro-technical depth (BACnet/LonWorks edge gateways, automated facade drone maintenance, and structural PINN telemetry). Released under the MIT License. Publicly accessible mit n<1K [View dataset](https://savrn.com/datasets/aegis-persona-sovereign-node) Dataset · Text to code ### [aegis-wgsl-webgpu-shaders](https://savrn.com/datasets/aegis-wgsl-webgpu-shaders) [Abdullah Ashraf](https://savrn.com/model-publishers/abdullahashraf122) The Aegis WGSL WebGPU Shader Instruction Dataset is a high-precision code-generation and conversational dataset mapping natural language physical simulation queries to executable WebGPU Shading Language (WGSL) compute and fragment shaders. Modern browsers and edge devices utilize WebGPU for 60-120 FPS hardware-accelerated scientific visualization. This dataset trains or fine-tunes LLMs to act as specialized graphics engineers capable of translating hydrodynamic, thermal, seismic, acoustic, and aeration queries directly into functional WGSL shader code. 1. Sentinel HUFP Fluid Dynamics: Eulerian fluid flow vectors, wave interference patterns, Navier-Stokes approximations, and coastal storm… Publicly accessible mit n<1K [View dataset](https://savrn.com/datasets/aegis-wgsl-webgpu-shaders) Dataset ### [ai-challenge](https://savrn.com/datasets/ai-challenge) [Khoatrinh](https://savrn.com/model-publishers/shineekuwu) Publicly accessible mit [View dataset](https://savrn.com/datasets/ai-challenge) Dataset ### [ai-training-companies](https://savrn.com/datasets/ai-training-companies) [Aitrainer.work](https://savrn.com/model-publishers/aitrainer-work) 54 companies that pay people to train and evaluate AI models: expert networks, crowdwork platforms and data vendors. One row per company, covering how it hires (AI interviews, assessments, ID checks), how it pays (payout frequency, payment methods, eligible countries), what work it offers (RLHF, model evaluation, red teaming, coding, annotation, speech data) and what its job listings pay. Version 2026.09.1, released 2026-09-29. Online edition with filters and field definitions: AI training companies dataset. - companies.csv: one row per company. Arrays are joined with;, nested objects become dotted columns (listings.active, payobservedhourlyusd.median). This is the file the viewer loads.… Publicly accessible cc-by-4.0 n<1K [View dataset](https://savrn.com/datasets/ai-training-companies) Dataset ### [ai231-smart-speaker](https://savrn.com/datasets/ai231-smart-speaker) [Justin Jose Ruaya](https://savrn.com/model-publishers/justinruaya123) Iris uses direct finite command recognition, our Hey Iris wake model, Silero VAD and a session-only speaker reference for one command. Recognition runs locally without ASR/STT transcription or a language model. Designed voices are synthetic and do not establish independent human, household or Raspberry Pi acceptance. Pinned data/source/license receipts, quantitative results and limitations follow. The preserved historical card records earlier experiments and source terms. The release uses immutable original recordings and explicitly labelled generated or constructed examples. reproduction-inputs.json is the machine-readable index of pinned files, source revisions, SHA-256 values, audio… Publicly accessible other [View dataset](https://savrn.com/datasets/ai231-smart-speaker) Dataset ### [ai_glasses](https://savrn.com/datasets/ai-glasses) [Yuzhen Chen](https://savrn.com/model-publishers/yuzhench) Access requested at publisher [View dataset](https://savrn.com/datasets/ai-glasses) Dataset ### [aide_elderly](https://savrn.com/datasets/aide-elderly) [Fabien Allemand](https://savrn.com/model-publishers/fabien-cea-list) Small dataset for experiments related to project Aide. - Fabien Allemand (fabien.allemand@cea.fr) Publicly accessible apache-2.0 [View dataset](https://savrn.com/datasets/aide-elderly) Dataset ### [aishell1](https://savrn.com/datasets/aishell1) [ModelEvolution](https://savrn.com/model-publishers/modelevolution) Access requested at publisher [View dataset](https://savrn.com/datasets/aishell1) Dataset · Tabular regression ### [alaska-arctic-hydrology-matrix](https://savrn.com/datasets/alaska-arctic-hydrology-matrix) [Abdullah Ashraf](https://savrn.com/model-publishers/abdullahashraf122) The Alaska Arctic Hydrology Harmonization Matrix is a multi-source geospatial hydro-climatic dataset containing 50,000 spatial coordinate vectors sampled across sub-arctic and hydrological basins. It unifies digital elevation models (DEM), permanent surface water occurrence percentages, seasonal water transition classifications, historical rainfall averages, and human demographic proxies into an aligned tabular feature matrix. This dataset was generated in-house via the LocalDataHarmonizer engine in ALASKASANDBOX, utilizing high-throughput spatial sampling algorithms (rasterio.sample.samplegen) to extract raster values at exact coordinate centroids. Distributed under the Creative Commons… Publicly accessible cc-by-4.0 10K