Skip to content

v0.6.0

Compare
Choose a tag to compare
@mattdangerw mattdangerw released this 11 Jul 04:20
· 75 commits to r0.6 since this release
de9a325

KerasNLP is adding experimental support for Jax and PyTorch backends on top of the Keras Core library. Read the anouncement, and browse the full library documentation, including how to specify the backend when running your code.

Support for both Jax and PyTorch is still experimental, expect some rough edges and please give us feedback!

Summary

  • This release should be equivalent to 0.5.2 with the addition of multi-backend support.
  • The following API symbols are currently restricted to the tensorflow backend:
    • keras_nlp.models.DebertaV3*
    • keras_nlp.models.FNet*
    • keras_nlp.metrics
    • keras_nlp.samplers.BeamSampler
    • keras_nlp.samplers.ContrastiveSampler
  • Note that there are two ways you can run on top of Tensorflow.
    • If you run your scripts/colab without any changes, KerasNLP will use tf.keras for all layer and modeling implementations. This should be a no-op from previous releases of the library.
    • If you run your scripts/colab with KERAS_BACKEND={jax, torch, tensorflow}, you will be trying the new Keras Core library, using the specified backend. This is a great way to test out the future of the library!
    • Full details on runtime specification is available along with the Keras Core documentation.

What's Changed

New Contributors

Full Changelog: v0.5.2...v0.6.0