Tutorials | TensorFlow Hub
https://www.tensorflow.org/hub/tutorials17.12.2020 · Getting started. TensorFlow Hub is a comprehensive repository of pre-trained models ready for fine-tuning and deployable anywhere. Download the latest trained models with a minimal amount of code with the tensorflow_hub library.. The following tutorials should help you getting started with using and applying models from TF Hub for your needs.
TensorFlow Hub
https://www.tensorflow.org/hubTensorFlow Hub is a repository of trained machine learning models. "mainly", "In the plain!"]) TensorFlow Hub is a repository of trained machine learning models ready for fine-tuning and deployable anywhere. Reuse trained models like BERT and Faster R …
tensorflow-hub · PyPI
pypi.org › project › tensorflow-hubApr 14, 2021 · tensorflow-hub 0.12.0. pip install tensorflow-hub. Copy PIP instructions. Latest version. Released: Apr 14, 2021. TensorFlow Hub is a library to foster the publication, discovery, and consumption of reusable parts of machine learning models. Project description.
tensorflow-hub · PyPI
https://pypi.org/project/tensorflow-hub14.04.2021 · tensorflow-hub 0.12.0. pip install tensorflow-hub. Copy PIP instructions. Latest version. Released: Apr 14, 2021. TensorFlow Hub is a library to foster the publication, discovery, and consumption of reusable parts of machine learning models. Project description.
Installation | TensorFlow Hub
https://www.tensorflow.org/hub/installation06.01.2022 · The tensorflow_hub library can be installed alongside TensorFlow 1 and TensorFlow 2. We recommend that new users start with TensorFlow 2 right away, and current users upgrade to it. Use with TensorFlow 2. Use pip to install TensorFlow 2 as usual. (See there for extra instructions about GPU support.)
TensorFlow Hub
www.tensorflow.org › hubTensorFlow Hub is a repository of trained machine learning models. "mainly", "In the plain!"]) TensorFlow Hub is a repository of trained machine learning models ready for fine-tuning and deployable anywhere. Reuse trained models like BERT and Faster R-CNN with just a few lines of code.