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https://github.com/tensorflow/hub

A library for transfer learning by reusing parts of TensorFlow models.
https://github.com/tensorflow/hub

embeddings image-classification machine-learning ml python tensorflow transfer-learning

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A library for transfer learning by reusing parts of TensorFlow models.

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README 

        



**TensorFlow Hub has moved to [Kaggle Models](https://kaggle.com/models)**



Starting November 15th 2023, links to [tfhub.dev](https://tfhub.dev) 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///")`. Although no

migration or code rewrites are explicitly required, we recommend replacing

tfhub.dev links with their Kaggle Models counterparts to improve code health and

debuggability. See FAQs [here](https://kaggle.com/tfhub-dev-faqs).



As of March 18, 2024, unmigrated model assets (see list below) were deleted and

retrieval is no longer possible. These unmigrated model assets include:



-   [inaturalist/vision/embedder/inaturalist_V2](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/inaturalist/models/vision/embedder/inaturalist_V2)

-   [nvidia/unet/industrial/class_1](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/nvidia/models/unet/industrial/class_1)

-   [nvidia/unet/industrial/class_2](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/nvidia/models/unet/industrial/class_2)

-   [nvidia/unet/industrial/class_3](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/nvidia/models/unet/industrial/class_3)

-   [nvidia/unet/industrial/class_4](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/nvidia/models/unet/industrial/class_4)

-   [nvidia/unet/industrial/class_5](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/nvidia/models/unet/industrial/class_5)

-   [nvidia/unet/industrial/class_6](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/nvidia/models/unet/industrial/class_6)

-   [nvidia/unet/industrial/class_7](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/nvidia/models/unet/industrial/class_7)

-   [nvidia/unet/industrial/class_8](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/nvidia/models/unet/industrial/class_8)

-   [nvidia/unet/industrial/class_9](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/nvidia/models/unet/industrial/class_9)

-   [nvidia/unet/industrial/class_10](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/nvidia/models/unet/industrial/class_10)

-   [silero/silero-stt/de](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/silero/models/silero-stt/de)

-   [silero/silero-stt/en](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/silero/models/silero-stt/en)

-   [silero/silero-stt/es](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/silero/models/silero-stt/es)

-   [svampeatlas/vision/classifier/fungi_mobile_V1](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/svampeatlas/models/vision/classifier/fungi_mobile_V1)

-   [svampeatlas/vision/embedder/fungi_V2](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/svampeatlas/models/vision/embedder/fungi_V2)



# tensorflow_hub



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.



## Getting Started



  * [Introduction](https://www.tensorflow.org/hub/)

  * The asset types of [tfhub.dev](https://tfhub.dev/)

      * [SavedModels for TensorFlow 2](docs/tf2_saved_model.md)

        and the [Reusable SavedModel interface](docs/reusable_saved_models.md).

      * Deprecated: [Models in TF1 Hub format](docs/tf1_hub_module.md) and

        their [Common Signatures](docs/common_signatures/index.md) collection.

  * Using the library

      * [Installation](docs/installation.md)

      * [Caching model downloads](docs/caching.md)

      * [Migration to TF2](docs/migration_tf2.md)

      * [Model compatibility for TF1/TF2](docs/model_compatibility.md)

      * [Common issues](docs/common_issues.md)

      * [Build from source](docs/build_from_source.md)

      * [Hosting a module](docs/hosting.md)

  * Tutorials

      * [TF2 Image Retraining](https://colab.research.google.com/github/tensorflow/hub/blob/master/examples/colab/tf2_image_retraining.ipynb)

      * [TF2 Text Classification](https://colab.research.google.com/github/tensorflow/hub/blob/master/examples/colab/tf2_text_classification.ipynb)

      * [Additional TF1 and TF2 examples](examples/README.md)



## Contributing



If you'd like to contribute to TensorFlow Hub, be sure to review the

[contribution guidelines](CONTRIBUTING.md). To contribute code to the

library itself (not examples), you will probably need to

[build from source](docs/build_from_source.md).



This project adheres to TensorFlow's

[code of conduct](https://github.com/tensorflow/tensorflow/blob/master/CODE_OF_CONDUCT.md).

By participating, you are expected to uphold this code.



We use [GitHub issues](https://github.com/tensorflow/hub/issues) for tracking

requests and bugs.



## License



[Apache License 2.0](LICENSE)