PyTorch is the deep-learning framework behind most of the models in this directory. If you train anything, you almost certainly train it here.
| Category | ML frameworks & MLOps |
| Type | Deep learning framework |
| License | NOASSERTION |
| Runs locally | Yes |
| Built with | Python |
| Skill level | Intermediate |
| Best for | anyone training or fine-tuning a model |
Other open-source ml frameworks & mlops tools worth comparing:
DagsterOrchestration that thinks in data assets, not tasks
TensorFlowGoogle's deep-learning framework, built for production
OpenCVThe computer vision library everything else builds on
scikit-learnClassical machine learning, done properly
Apache AirflowSchedule and monitor data pipelines
RayScale Python from a laptop to a cluster
JAXNumPy with autodiff, JIT and TPUs
XGBoostStill the one to beat on tabular data
Label StudioLabel anything — text, images, audio, video
MLflowTrack experiments and ship models without the spreadsheet
ONNXMove a model between frameworks and runtimes
LightGBMGradient boosting that trains fast on big tables
CVATSerious annotation for computer vision
DVCGit for datasets and models
OptunaFind the right hyperparameters without guessingPyTorch is free and open-source (NOASSERTION license), so you can use, self-host and modify it at no cost.
Yes. PyTorch is designed to run on your own machine or server, keeping your data private.
Popular open-source alternatives include Dagster, TensorFlow, OpenCV. See the comparisons above to choose.
Browse the full directory of open-source AI tools, models and projects — updated daily.
Browse all tools →