TensorFlow Hub is a repository of trained machine learning models.
!pip install --upgrade tensorflow_hub import tensorflow_hub as hub model = hub.KerasLayer("https://tfhub.dev/google/nnlm-en-dim128/2") embeddings = model(["The rain in Spain.", "falls", "mainly", "In the plain!"]) print(embeddings.shape) #(4,128)
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.
See the guideLearn about how to use TensorFlow Hub and how it works.
See tutorialsTutorials show you end-to-end examples using TensorFlow Hub.
See modelsFind trained TF, TFLite, and TF.js models for your use case.
Find trained models from the TensorFlow community on TFHub.dev
Use the Faster R-CNN Inception ResNet V2 640x640 model for detecting objects in images.
News & announcements
Check out our blog for more announcements and view the latest #TFHub updates on Twitter
TensorFlow Hub for Real World Impact at Google I/O
Learn how you can use TensorFlow Hub to build ML solutions with real world impact.
On-device ML solutions
To explore ML solutions for your mobile and web apps including TensorFlow Hub, visit the Google on-device machine learning page.
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Learn how to use the SPICE model to automatically transcribe sheet music from live audio.
Join the TensorFlow Hub community