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
  • Installation
  • Caching model downloads
  • Migration to TF2
  • Model compatibility for TF1/TF2
  • Common issues
  • Build from source
  • Hosting a module
• Tutorials
  • TF2 Image Retraining
  • TF2 Text Classification
  • Additional TF1 and TF2 examples

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.

Apache License 2.0