# hub

**Repository Path**: mirrors_tensorflow/hub

## Basic Information

- **Project Name**: hub
- **Description**: A library for transfer learning by reusing parts of TensorFlow models.
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-08-22
- **Last Updated**: 2026-02-21

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

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g3doc/_index.yaml is rendered on tensorflow.org/hub.
Both link to g3doc/overview.md and g3doc/*.md for detailed docs.
-->

**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/<publisher>/<model>/<version>")`. 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](https://github.com/tensorflow/docs/blob/master/site/en/hub/tf2_saved_model.md)
        and the [Reusable SavedModel interface](https://github.com/tensorflow/docs/blob/master/site/en/hub/reusable_saved_models.md).
      * Deprecated: [Models in TF1 Hub format](https://github.com/tensorflow/docs/blob/master/site/en/hub/tf1_hub_module.md)
        and their [Common Signatures](https://github.com/tensorflow/docs/blob/master/site/en/hub/common_signatures/index.md)
        collection.
  * Using the library
      * [Installation](https://github.com/tensorflow/docs/blob/master/site/en/hub/installation.md)
      * [Caching model downloads](https://github.com/tensorflow/docs/blob/master/site/en/hub/caching.md)
      * [Migration to TF2](https://github.com/tensorflow/docs/blob/master/site/en/hub/migration_tf2.md)
      * [Model compatibility for TF1/TF2](https://github.com/tensorflow/docs/blob/master/site/en/hub/model_compatibility.md)
      * [Common issues](https://github.com/tensorflow/docs/blob/master/site/en/hub/common_issues.md)
      * [Build from source](https://github.com/tensorflow/docs/blob/master/site/en/hub/build_from_source.md)
      * [Hosting a module](https://github.com/tensorflow/docs/blob/master/site/en/hub/hosting.md)
  * Tutorials
      * [TF2 Image Retraining](https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/hub/tutorials/tf2_image_retraining.ipynb)
      * [TF2 Text Classification](https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/hub/tutorials/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](https://github.com/tensorflow/docs/blob/master/site/en/hub/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)