TensorFlow Hub is moving to Kaggle Models.
Starting November 15th, links to tfhub.dev will redirect to
their counterparts on Kaggle Models. tensorflow_hub will continue to support
downloading models that were initially uploaded to tfhub.dev via e.g.
hub.load("https://tfhub.dev/<publisher>/<model>"). Although no migration or
code rewrites are explicitly required, we recommend replacing tfhub.dev links
with their Kaggle Models counterparts before November 15th to improve code
health and debuggability.
TensorFlow Hub is a repository of reusable assets for machine learning with TensorFlow. In particular, it provides pre-trained SavedModels that can be reused to solve new tasks with less training time and less training data.
This GitHub repository hosts the tensorflow_hub Python library to download
and reuse SavedModels in your TensorFlow program with a minimum amount of code,
as well as other associated code and documentation.
- Introduction
- The asset types of tfhub.dev
- SavedModels for TensorFlow 2 and the Reusable SavedModel interface.
- Deprecated: Models in TF1 Hub format and their Common Signatures collection.
- Using the library
- Tutorials
If you'd like to contribute to TensorFlow Hub, be sure to review the contribution guidelines. To contribute code to the library itself (not examples), you will probably need to build from source.
This project adheres to TensorFlow's code of conduct. By participating, you are expected to uphold this code.
We use GitHub issues for tracking requests and bugs.