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
3,164 datasets, sorted by most downloaded.
This dataset was created using LeRobot. Dataset Structure "codebaseversion": "v3.0", "fps": 30, "features": { "action": { "dtype": "float32", "names": [ "shoulderpan.pos", "shoulderlift.pos", "elbowflex.pos", "wristflex.pos", "wristroll.pos", "gripper.pos" "shape": [ 6
Apache TsFile version of argus-systems/pickup-carrot-remove-parquet-metadata-2. A Trossen AI stationary-arm dataset for a single pick-and-place task: pick up a carrot and put it in the bowl. Each frame records the 14-D dual-arm action and 14-D observation state. Task (taskindex 0): "Pick up carrot and put it in the bowl". Note: the source meta/info.json and meta/episodes.jsonl declare 61 episodes / 27,261 frames, but the source repository only contains 58 data/chunk-000/episode.parquet files (episodes 0, 39 and 50 are absent); the 58 present episodes (25,922 frames) were converted. - Time (INT64, milliseconds) - per-episode sample time, round(timestamp 1000) in milliseconds (the source…
This dataset was created using LeRobot.
This dataset was created using LeRobot.
Bro, imagine a dataset of 43 non-destructive attack payloads across 8 bug classes — 24 of them polyglot, meaning a single string that's simultaneously plausible HTML, JS, SQL and shell, so it escapes whatever context your app dropped it into. Plus real detector output from a full multimodal scan. Everything here is synthesised or locally generated. No real-world traffic, no scraped data, no user data. Each config ships JSONL and Parquet, so both of these work: Every payload carries a unique marker (PBHX7) so reflection is unambiguous — that's what makes these usable as training signal for a detector or as a fixture in your own test suite. This is a defensive dataset. Concretely: Every…
Processed data and prebuilt search indexes for the Product Search RAG app. This repository hosts build artifacts for that app, not a general-purpose dataset. The app downloads these files at startup, since they are too large to keep in its git repository. Derived from the Appliances category of the Amazon Reviews 2023 dataset collected by McAuley Lab. Use of this data follows the terms of the original dataset. Please cite the original authors: parentasin, producttitle, features, description, categories, details, price, derivedavgrating, nreviews, reviewtext, candidatereviewtitle, candidatereviewtext, candidatereviewhelpfulvote See the project repository for the full pipeline (make process…
Model Collections
Hand-picked starting points, each with the reason it exists.
Collection · 4 entries
Embedding models for retrieval
Sentence and document embedding models used to build retrieval systems. Dimension and sequence length matter more than size here, and both come from the publisher.
Collection · 4 entries
Models that fit on one accelerator
Models whose publisher-reported parameter count puts them within reach of a single accelerator at common precisions. Memory needed depends on precision and serving configuration, so treat the parameter count as the starting point, not the answer.
Collection · 6 entries
Open-weight text models worth knowing
Widely used open-weight language models, chosen because each one is a distinct family rather than a variant of the one above it. Selection, not a ranking.
Collection · 3 entries
Speech and audio models
Recognition and synthesis models, grouped so the two directions are easy to compare.
Related SAVRN Research
The hub sits beside SAVRN's market data and infrastructure research: what models cost to run, and what it takes to run them.
SAVRN Index
What open models cost to run
The same open-weight model priced by every host that serves it, per million tokens.
Research Hub
Data center trackers and maps
Moratoriums, permits, power, water and capital behind the facilities that run these models.
Method
How the Model Hub is built
Sources, evidence labels, refresh behaviour, and the limits of every comparison here.