# Datasets, Page 119 of 132 Source: https://savrn.com/datasets/page/119 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 ### [mit67_standard_resnet50_gap_oof_features](https://savrn.com/datasets/mit67-standard-resnet50-gap-oof-features) [Quoc Nil Nguyen](https://savrn.com/model-publishers/nilnguyen2k) Publicly accessible [View dataset](https://savrn.com/datasets/mit67-standard-resnet50-gap-oof-features) Dataset ### [ml-charts74](https://savrn.com/datasets/ml-charts74) [Finn Weber](https://savrn.com/model-publishers/wweberfinn) A documented Charts data-preparation workflow for Image Depth records. The bundled rows demonstrate the schema and validation path rather than pretending to be a full training corpus. - loaddata.py — loading, cleaning, and split preparation code. - datasetinfos.json — schema and split metadata. - metadatasample.jsonl — small, human-readable records for checking the schema. - README.md — data card and usage notes. Before using the prepared data, verify source licenses, duplicates across splits, missing values, label balance, and modality-specific corruption. Record the source version and every filtering rule so a later run can reproduce the same rows. The repository is suitable for testing… Publicly accessible mit [View dataset](https://savrn.com/datasets/ml-charts74) Dataset ### [mmd](https://savrn.com/datasets/mmd) [Shivlal6660jyoti](https://savrn.com/model-publishers/shivlal6660jyoti) Access requested at publisher cc-by-2.0 [View dataset](https://savrn.com/datasets/mmd) Dataset ### [mmml-fall2026-proposal-subset](https://savrn.com/datasets/mmml-fall2026-proposal-subset) [Jiatao Li](https://savrn.com/model-publishers/leejamesssss) Three archives from Meta's Seamless Interaction Naturalistic training split, used in our CMU 11-777 project proposal. The subset contains 37 participant-side recordings from 27 participant identifiers, totaling 3.20 GB. Each recording includes MP4, WAV, NPZ and JSON files. Archives were selected in order; this is a convenience sample. - naturalistic/train/0012/0000.tar - naturalistic/train/0012/0001.tar - naturalistic/train/0012/0002.tar - manifest.json: file sizes, SHA256 hashes and source URLs. The archives are unchanged copies of the source files. Recording counts are before motion-quality and synchronized-window filtering. Seamless Interaction is provided by Meta under CC BY-NC 4.0.… Publicly accessible cc-by-nc-4.0 [View dataset](https://savrn.com/datasets/mmml-fall2026-proposal-subset) Dataset ### [mockbuster-restricted-sample](https://savrn.com/datasets/mockbuster-restricted-sample) [Shuyi Chen](https://savrn.com/model-publishers/abigail99216) mockbuster 识别项目的两侧限定样本（此包供云端 GPU 计算标题 / 简介 / 海报相似度）。 双侧有海报且有 overview，共 70,733,031 对。两侧同时施加样本定义后： - 分片顺序即文件名字典序（part00 → part07）。 - 整包校验：sha256sum postersrestricted.tar 应等于 15d588589553f7edee12c2ca9580adceebb7d62a02640897a3523008b3500ee1。 - 逐片校验见 partsmanifest.tsv；tar 内结构为 posters/.jpg（原创）与 posterscand/cand.jpg（候选）。 - 标题相似度：用北美英语发行片名（origtitle / candtitle）。 - 简介相似度：用 origoverview / candoverview。 - 海报相似度：posters/.jpg 与 posterscand/cand.jpg。 - pairs.tsv.gz 的 daysdiff / arrival 基于 usanymin（含影展首映）；商业发行日口径见同表 canduscommercialmin 列。 - 候选侧池为英语池（originallanguage=='en'），不含非英语候选。 Publicly accessible [View dataset](https://savrn.com/datasets/mockbuster-restricted-sample) Dataset ### [mod_stress](https://savrn.com/datasets/mod-stress) [Alex Karachun](https://savrn.com/model-publishers/alexkarachun) Publicly accessible [View dataset](https://savrn.com/datasets/mod-stress) Dataset ### [moitruong123](https://savrn.com/datasets/moitruong123) [Lehung](https://savrn.com/model-publishers/le-hung) Dataset phục vụ cho nghiên cứu và huấn luyện mô hình AI. Dataset được lưu dưới dạng CSV. Publicly accessible [View dataset](https://savrn.com/datasets/moitruong123) Dataset ### [mono_train](https://savrn.com/datasets/mono-train) [Jing Cao](https://savrn.com/model-publishers/nosmall) Publicly accessible [View dataset](https://savrn.com/datasets/mono-train) Dataset ### [moodly-watch-index](https://savrn.com/datasets/moodly-watch-index) [Daniel](https://savrn.com/model-publishers/devlufero) Publicly accessible other [View dataset](https://savrn.com/datasets/moodly-watch-index) Dataset ### [mouse-dataset-30task-70random](https://savrn.com/datasets/mouse-dataset-30task-70random) [Micah Rentschler](https://savrn.com/model-publishers/micahr234) Publicly accessible [View dataset](https://savrn.com/datasets/mouse-dataset-30task-70random) Dataset ### [movie-file](https://savrn.com/datasets/movie-file) [Jaynestv](https://savrn.com/model-publishers/jaynesmaxtv) Publicly accessible [View dataset](https://savrn.com/datasets/movie-file) Dataset ### [msav-25k](https://savrn.com/datasets/msav-25k) [Lehan Shen](https://savrn.com/model-publishers/shenlehan) Publicly accessible [View dataset](https://savrn.com/datasets/msav-25k) Dataset ### [msmarco-DenseOn-128](https://savrn.com/datasets/msmarco-denseon-128) [Ian Muchina](https://savrn.com/model-publishers/much1na) MSMARCO docs + queries with pre-computed 768-dim label embeddings. - docs were kept only if they tokenize to ≤ 128 tokens (bert-base-uncased vocab). Publicly accessible apache-2.0 [View dataset](https://savrn.com/datasets/msmarco-denseon-128) Dataset · Text generation ### [mt-dialogues-100k-v1](https://savrn.com/datasets/mt-dialogues-100k-v1) [Koushik Reddy](https://savrn.com/model-publishers/koushik12311) 39,996 synthetic doctor/patient dialogues, generated from for supervised fine-tuning. Each one turns a single question-and-answer row of the source corpus into a conversation where a clinician has to elicit the case before answering it. The cases are included so the run can be reproduced, re-scored, or regenerated with another model. A dialogue file on its own cannot be. Three participants, isolated by construction rather than by instruction: - doctor — sees the opening line and the question it must answer. Nothing else. It chooses each turn whether to ask, to examine, or to conclude, and deciding it has enough is the capability being taught. - patient — holds the spoken facts and discloses… Publicly accessible apache-2.0 10K