# Datasets, Page 104 of 136 Source: https://savrn.com/datasets/page/104 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 ### [Poketwo-Spawn-Images](https://savrn.com/datasets/poketwo-spawn-images) [Eeveebot](https://savrn.com/model-publishers/eeveebot) Publicly accessible [View dataset](https://savrn.com/datasets/poketwo-spawn-images) Dataset ### [PoliteChatDataset](https://savrn.com/datasets/politechatdataset) [Reiwa-AI K.K.](https://savrn.com/model-publishers/reiwa-ai) This dataset is a collection of datasets intended for various language models, with response formats standardized using an LLM. The reformatting process preserves the writing style and persona of the original responses; the responses were not generated by the LLM from scratch. The aim is to have the model acquire basic knowledge and common sense during the initial phase of SFT (Supervised Fine-Tuning). This dataset contains LLM-transformed records derived from multiple source datasets with different licenses. - original-license: the license applicable to the original source - source: the URL from which the source data was obtained The original response text was stylistically rewritten by an… Publicly accessible other [View dataset](https://savrn.com/datasets/politechatdataset) Dataset · Reinforcement learning ### [PortSimEnv-AgentEnv](https://savrn.com/datasets/portsimenv-agentenv) [Edgar Arakelyan](https://savrn.com/model-publishers/earakely-scale) call, an emergency, late ships, a crane outage, a gale and bunched arrivals come in as bulletins, and the tug company and the pilot station announce 2 tugs and 2 pilots out from hour 54. It ends at the hindsight optimum (reward 1.0), where a naive re-plan breaks the rules. on the replay Space. Twin © OpenStreetMap contributors (ODbL). An agent runs one container quay at the Port of Barcelona for a week of 2024 that has just gone wrong: late and bunched ships, closed quay sections, crane breakdowns, gales, emergencies. It decides when, where along the quay and with how many cranes every ship docks, and the week is graded deterministically against a plan CP-SAT proved optimal. This dataset… Publicly accessible cc-by-sa-4.0 n<1K [View dataset](https://savrn.com/datasets/portsimenv-agentenv) Dataset ### [ProRiboGen-datasets](https://savrn.com/datasets/proribogen-datasets) [Yuhua Jiao](https://savrn.com/model-publishers/yuhuajiaotky) Publicly accessible [View dataset](https://savrn.com/datasets/proribogen-datasets) Dataset ### [ProbRoPE](https://savrn.com/datasets/probrope) [Zihao Zou](https://savrn.com/model-publishers/zihaozou) Publicly accessible [View dataset](https://savrn.com/datasets/probrope) Dataset ### [Project-AHON](https://savrn.com/datasets/project-ahon) [Manuel](https://savrn.com/model-publishers/jess-christine) Publicly accessible mit [View dataset](https://savrn.com/datasets/project-ahon) Dataset ### [Project_1_lexicon_and_topic_model](https://savrn.com/datasets/project-1-lexicon-and-topic-model) [Ashly Caicedo Cortes](https://savrn.com/model-publishers/ashcaicor) Course: FTEC 6V96 · Financial NLP & Textual Analysis · Author: Ashly Caicedo This project builds a story from two earlier homeworks, HW1 (a data-driven sentiment lexicon compared against TextBlob, VADER and Loughran-McDonald) and HW2 (RBM topic modelling), on a dataset of S&P 500, Dow and NASDAQ news headlines. As the assignment requires, it changes the target variable, the tokenization technique and the ML approach, and reports metrics on the train, test and inference partitions. HW1, the lexicon's edge was the market's mood. The custom lexicon beat all three benchmarks on train and test but lost on inference (0.604 vs. 0.623 precision). In October 2020 the market rose on 62% of days, and… Publicly accessible [View dataset](https://savrn.com/datasets/project-1-lexicon-and-topic-model) Dataset ### [PubTabNet](https://savrn.com/datasets/pubtabnet) [Gia Huy](https://savrn.com/model-publishers/yaqi2) Publicly accessible [View dataset](https://savrn.com/datasets/pubtabnet) Dataset ### [QA_test_question_set_for_CEE](https://savrn.com/datasets/qa-test-question-set-for-cee) [Xiaohan](https://savrn.com/model-publishers/cxh1212) (1) The CEE-QA test question set comprises 1,200 questions from Registered Construction Engineer Examinations (RCEEs) and 1,881 self-designed questions covering 18 second-level knowledge sub-domains (KSD) by experts. (2) Each question from the CEE-QA test question set are manually annotated with four features, including the question source, single-answer question or multiple-answer question, and calculation question or non-calculation question. (3) This CEE-QA test question set is developed and maintained by Southeast University. (4) Make sure to read the specification and follow the rules. The answers could be submitted through… Access requested at publisher mit [View dataset](https://savrn.com/datasets/qa-test-question-set-for-cee) Dataset ### [QSolver_Dataset](https://savrn.com/datasets/qsolver-dataset) [Syzygy](https://savrn.com/model-publishers/a-01a) Publicly accessible mit [View dataset](https://savrn.com/datasets/qsolver-dataset) Dataset · Text generation ### [QWE](https://savrn.com/datasets/qwe) [SHRIJAN KUMAR TIWARI](https://savrn.com/model-publishers/shrijanagain) Instruction-tuning dataset with chain-of-thought, merged and deduplicated from multiple public reasoning datasets. Every row is JSON with: - instruction - the user/task prompt - thought - reasoning wrapped in tags (always present) - response - the final answer - hasthinking - always true - sourcedataset - provenance of the row in row order. Sources include OpenThoughts3-1.2M, Mixture-of-Thoughts, Infinity-Instruct and Nemotron-Post-Training-Dataset (v1 and v2). Deduplication is exact full-line (md5), applied globally across all sources. - All model-identity references were normalized to "Speed by SKT AI LABS Private Limited". - A small fraction of rows (mostly from one legacy source) carry… Publicly accessible apache-2.0 100B