A TensorFlow 2.11.0 Keras implementation of BERT.
Project description
BERT for TensorFlow 2.11.0
This is a modification version of the original bert-for-tf2
created by kpe
. I made a minor change to the code
to make it work with never version of TensorFlow, following the solution that i found in github community.
Resolving the TypeError issue. Last time checked at 1/23/2023 - it worked fine.
This repo contains a TensorFlow 2.11.0
_ Keras
_ implementation of google-research/bert
_
with support for loading of the original pre-trained weights
_,
and producing activations numerically identical to the one calculated by the original model.
ALBERT
_ and adapter-BERT
_ are also supported by setting the corresponding
configuration parameters (shared_layer=True
, embedding_size
for ALBERT
_
and adapter_size
for adapter-BERT
_). Setting both will result in an adapter-ALBERT
by sharing the BERT parameters across all layers while adapting every layer with layer specific adapter.
The implementation is build from scratch using only basic tensorflow operations,
following the code in google-research/bert/modeling.py
_
(but skipping dead code and applying some simplifications). It also utilizes kpe/params-flow
_ to reduce
common Keras boilerplate code (related to passing model and layer configuration arguments).
bert-for-tf2e
_ should work with both TensorFlow 2.11.0
_ and TensorFlow 1.14
_ or newer.
Install
bert-for-tf2e
bert for tensorflow 2.0 (extended) is on the Python Package Index (PyPI):
::
pip install bert-for-tf2e
For more detail please check the original version:
SOURCE
_ - https://github.com/kpe/bert-for-tf2
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