mirror of https://github.com/tensorflow/hub.git
99 lines
6.4 KiB
Markdown
99 lines
6.4 KiB
Markdown
<!-- Copyright 2018 The TensorFlow Hub Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================-->
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<!--
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This file is rendered on github.com/tensorflow/hub.
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g3doc/_index.yaml is rendered on tensorflow.org/hub.
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Both link to g3doc/overview.md and g3doc/*.md for detailed docs.
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-->
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**TensorFlow Hub has moved to [Kaggle Models](https://kaggle.com/models)**
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Starting November 15th 2023, links to [tfhub.dev](https://tfhub.dev) redirect to
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their counterparts on Kaggle Models. `tensorflow_hub` will continue to support
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downloading models that were initially uploaded to tfhub.dev via e.g.
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`hub.load("https://tfhub.dev/<publisher>/<model>/<version>")`. Although no
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migration or code rewrites are explicitly required, we recommend replacing
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tfhub.dev links with their Kaggle Models counterparts to improve code health and
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debuggability. See FAQs [here](https://kaggle.com/tfhub-dev-faqs).
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As of March 18, 2024, unmigrated model assets (see list below) were deleted and
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retrieval is no longer possible. These unmigrated model assets include:
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- [inaturalist/vision/embedder/inaturalist_V2](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/inaturalist/models/vision/embedder/inaturalist_V2)
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- [nvidia/unet/industrial/class_1](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/nvidia/models/unet/industrial/class_1)
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- [nvidia/unet/industrial/class_2](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/nvidia/models/unet/industrial/class_2)
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- [nvidia/unet/industrial/class_3](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/nvidia/models/unet/industrial/class_3)
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- [nvidia/unet/industrial/class_4](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/nvidia/models/unet/industrial/class_4)
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- [nvidia/unet/industrial/class_5](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/nvidia/models/unet/industrial/class_5)
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- [nvidia/unet/industrial/class_6](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/nvidia/models/unet/industrial/class_6)
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- [nvidia/unet/industrial/class_7](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/nvidia/models/unet/industrial/class_7)
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- [nvidia/unet/industrial/class_8](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/nvidia/models/unet/industrial/class_8)
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- [nvidia/unet/industrial/class_9](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/nvidia/models/unet/industrial/class_9)
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- [nvidia/unet/industrial/class_10](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/nvidia/models/unet/industrial/class_10)
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- [silero/silero-stt/de](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/silero/models/silero-stt/de)
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- [silero/silero-stt/en](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/silero/models/silero-stt/en)
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- [silero/silero-stt/es](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/silero/models/silero-stt/es)
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- [svampeatlas/vision/classifier/fungi_mobile_V1](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/svampeatlas/models/vision/classifier/fungi_mobile_V1)
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- [svampeatlas/vision/embedder/fungi_V2](https://github.com/tensorflow/tfhub.dev/tree/master/assets/docs/svampeatlas/models/vision/embedder/fungi_V2)
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# tensorflow_hub
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This GitHub repository hosts the `tensorflow_hub` Python library to download
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and reuse SavedModels in your TensorFlow program with a minimum amount of code,
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as well as other associated code and documentation.
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## Getting Started
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* [Introduction](https://www.tensorflow.org/hub/)
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* The asset types of [tfhub.dev](https://tfhub.dev/)
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* [SavedModels for TensorFlow 2](https://github.com/tensorflow/docs/blob/master/site/en/hub/tf2_saved_model.md)
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and the [Reusable SavedModel interface](https://github.com/tensorflow/docs/blob/master/site/en/hub/reusable_saved_models.md).
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* Deprecated: [Models in TF1 Hub format](https://github.com/tensorflow/docs/blob/master/site/en/hub/tf1_hub_module.md)
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and their [Common Signatures](https://github.com/tensorflow/docs/blob/master/site/en/hub/common_signatures/index.md)
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collection.
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* Using the library
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* [Installation](https://github.com/tensorflow/docs/blob/master/site/en/hub/installation.md)
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* [Caching model downloads](https://github.com/tensorflow/docs/blob/master/site/en/hub/caching.md)
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* [Migration to TF2](https://github.com/tensorflow/docs/blob/master/site/en/hub/migration_tf2.md)
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* [Model compatibility for TF1/TF2](https://github.com/tensorflow/docs/blob/master/site/en/hub/model_compatibility.md)
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* [Common issues](https://github.com/tensorflow/docs/blob/master/site/en/hub/common_issues.md)
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* [Build from source](https://github.com/tensorflow/docs/blob/master/site/en/hub/build_from_source.md)
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* [Hosting a module](https://github.com/tensorflow/docs/blob/master/site/en/hub/hosting.md)
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* Tutorials
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* [TF2 Image Retraining](https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/hub/tutorials/tf2_image_retraining.ipynb)
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* [TF2 Text Classification](https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/hub/tutorials/tf2_text_classification.ipynb)
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* [Additional TF1 and TF2 examples](examples/README.md)
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## Contributing
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If you'd like to contribute to TensorFlow Hub, be sure to review the
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[contribution guidelines](CONTRIBUTING.md). To contribute code to the
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library itself (not examples), you will probably need to
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[build from source](https://github.com/tensorflow/docs/blob/master/site/en/hub/build_from_source.md).
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This project adheres to TensorFlow's
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[code of conduct](https://github.com/tensorflow/tensorflow/blob/master/CODE_OF_CONDUCT.md).
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By participating, you are expected to uphold this code.
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We use [GitHub issues](https://github.com/tensorflow/hub/issues) for tracking
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requests and bugs.
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## License
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[Apache License 2.0](LICENSE)
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