v0.4.1 #775
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mattdangerw
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v0.4.1
#775
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@mattdangerw We also fixed Mistake in projection layer dimension of MaskedLMHead #733 through #725 |
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@shivance indeed we did! Though actually we are not exposing the new The fix for |
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The 0.4.1 release is a minor release with new model architectures and compilation defaults for task models. If you encounter any problems or have questions, please open an issue!
Summary
keras_nlp.models.BertClassifier). No existing functionality is changed, but users of task models can now skip calling.compile()and use default learning rates and optimizer strategies provided by the library.keras_nlp.models.AlbertBackbone,keras_nlp.models.AlbertClassifier, preprocessor, and tokenizer layers for pre-trained ALBERT models.keras_nlp.models.FNetBackbone,keras_nlp.models.FNetClassifier, preprocessor, and tokenizer layers for pre-trained FNet models.keras_nlp.models.DebertaV3Backbone,keras_nlp.models.DebertaV3Classifier, preprocessor, and tokenizer layers for pre-trained DeBERTaV3 models.What's Changed
selfin calls tosuper()by @mbrukman in Clean up class name andselfin calls tosuper()#628Backbonebase class by @jbischof in CreateBackbonebase class #621value_diminTransformerDecoder's cross-attn layer by @abheesht17 in Fixvalue_diminTransformerDecoder's cross-attn layer #667token_embeddingas a Backbone Property by @abheesht17 in Exposetoken_embeddingas a Backbone Property #676from_presetto base tokenizer classes by @shivance in Movefrom_presetto base tokenizer classes #673AlbertClassifierby @shivance in AddAlbertClassifier#668GPT2Preprocessorby @chenmoneygithub in Add start/end token padding toGPT2Preprocessor#704New Contributors
selfin calls tosuper()#628from_presetto base tokenizer classes #673Full Changelog: v0.4.0...v0.4.1
This discussion was created from the release v0.4.1.
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