BERT-keras | Keras implementation of BERT with pre-trained weights | Machine Learning library

by Separius Python Version: Current License: GPL-3.0

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | BERT-keras Summary

BERT-keras is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, Keras, Transformer applications. BERT-keras has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has medium support. However BERT-keras build file is not available. You can download it from GitHub.

Status: Archive (code is provided as-is, no updates expected).

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Quality

Security

License

Reuse

Support

BERT-keras has a medium active ecosystem.

It has 825 star(s) with 204 fork(s). There are 30 watchers for this library.

It had no major release in the last 6 months.

There are 7 open issues and 16 have been closed. On average issues are closed in 3 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of BERT-keras is current.

Quality

BERT-keras has 0 bugs and 24 code smells.

Security

BERT-keras has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

BERT-keras code analysis shows 0 unresolved vulnerabilities.

There are 10 security hotspots that need review.

License

BERT-keras is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

BERT-keras releases are not available. You will need to build from source code and install.

BERT-keras has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

BERT-keras saves you 669 person hours of effort in developing the same functionality from scratch.

It has 1551 lines of code, 117 functions and 15 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed BERT-keras and discovered the below as its top functions. This is intended to give you an instant insight into BERT-keras implemented functionality, and help decide if they suit your requirements.

Generate sentences from text corpus
Return a copy of the given sentence
Create a sentence batch from a list of tokens
Create a TaskDataBatch from a list of sentences
Evaluate the gradient
Clean the keras module
Compute TPU compatible variables
Replace keras
Remove kas modules from sys modules
Calculate the attention layer
Multihead attention layer
Return the shape of x
Reshape x

Get all kandi verified functions for this library.

BERT-keras Key Features

No Key Features are available at this moment for BERT-keras.

BERT-keras Examples and Code Snippets

No Code Snippets are available at this moment for BERT-keras.

Community Discussions

Trending Discussions on BERT-keras

Improving BERT by training on additional data

QUESTION

Improving BERT by training on additional data

Asked 2019-Oct-02 at 10:59

I have a BERT multilanguage model from Google. And I have a lot of text data in my language (Korean). I want BERT to make better vectors for texts in this language. So I want to additionally train BERT on that text corpus I have. Like if I would have w2v model trained on some data and would want to continue training it. Is it possible with BERT?

There are a lot of examples of "fine-tuning" BERT on some specific tasks like even the original one from Google where you can train BERT further on your data. But as far as I understand it (I might be wrong) we do it within our task-specified model (for classification task for example). So... we do it at the same time as training our classifier (??)

What I want is to train BERT further separately and then get fixed vectors for my data. Not to build it into some task-specified model. But just get vector representation for my data (using get_features function) like they do in here. I just need to train the BERT model additionally on more data of the specific language.

Would be endlessly grateful for any suggestions/links on how to train BURT model further (preferably Tensorflow). Thank you.

...

ANSWER

Answered 2019-Sep-30 at 13:34

Package transformers provides code for using and fine-tuning of most currently popular pre-trained Transformers including BERT, XLNet, GPT-2, ... You can easily load the model and continue training.

You can get the multilingual BERT model:

Source https://stackoverflow.com/questions/58155390

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install BERT-keras

You can download it from GitHub.
You can use BERT-keras like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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