Skip to main content

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:

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

bert_for_tf2e-0.14.13-py3-none-any.whl (48.2 kB view details)

Uploaded Python 3

File details

Details for the file bert_for_tf2e-0.14.13-py3-none-any.whl.

File metadata

File hashes

Hashes for bert_for_tf2e-0.14.13-py3-none-any.whl
Algorithm Hash digest
SHA256 50c92a69fcf0147bcb0e3f4327397000c69ebb38a50fd85b8be03c37ee419137
MD5 f04ed1d6f9dce4b4852efc09e4dc518f
BLAKE2b-256 490d88c29004e79a1727d38a8a5df6df238748f4a7b9130e37681a38c8321afc

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page