bert-embedding | 🔡 Token level embeddings from BERT model | Natural Language Processing library

by imgarylai Python Version: 1.0.1 License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | bert-embedding Summary

bert-embedding is a Python library typically used in Artificial Intelligence, Natural Language Processing, Bert, Transformer applications. bert-embedding has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Token level embeddings from BERT model on mxnet and gluonnlp

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bert-embedding has a low active ecosystem.

It has 451 star(s) with 67 fork(s). There are 8 watchers for this library.

It had no major release in the last 6 months.

bert-embedding has no issues reported. On average issues are closed in 26 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of bert-embedding is 1.0.1

Quality

bert-embedding has 0 bugs and 0 code smells.

Security

bert-embedding has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

bert-embedding code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

bert-embedding is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

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

Build file is available. You can build the component from source.

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

bert-embedding saves you 143 person hours of effort in developing the same functionality from scratch.

It has 358 lines of code, 17 functions and 9 files.

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

Top functions reviewed by kandi - BETA

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

Setup Babel package
Get the development version
Get the full version information for a given file
Writes the version information to a file

Get all kandi verified functions for this library.

bert-embedding Key Features

No Key Features are available at this moment for bert-embedding.

bert-embedding Examples and Code Snippets

No Code Snippets are available at this moment for bert-embedding.

Community Discussions

Trending Discussions on bert-embedding

How to get BioBERT embeddings

Manipulating tensorflow code to add different layers

Undefined symbol when importing tf-sentencepiece

QUESTION

How to get BioBERT embeddings

Asked 2021-Feb-21 at 09:46

I have field within a pandas dataframe with a text field for which I want to generate BioBERT embeddings. Is there a simple way with which I can generate the vector embeddings? I want to use them within another model.

here is a hypothetical sample of the data frame

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I have tried this package, but receive an error upon installation https://pypi.org/project/biobert-embedding

Error:

...

ANSWER

Answered 2021-Feb-21 at 09:46

Try to install it as follows:

Source https://stackoverflow.com/questions/66284360

QUESTION

Manipulating tensorflow code to add different layers

Asked 2020-Jan-16 at 23:09

I am experimenting with BERT embeddings for text classification. I am using this code that creates a BERT embedding layer and a dense layer for binary classification.

...

ANSWER

Answered 2020-Jan-16 at 23:09

First, make batch size smaller.

Then change to this: this adds a global max pooling 1d layer to flatten out.

Source https://stackoverflow.com/questions/59757979

QUESTION

Undefined symbol when importing tf-sentencepiece

Asked 2020-Jan-14 at 08:53

On my MacBook (version 10.14.6) I am succesfully running a Django application including TensorFlow and tf-sentencepiece (in particular to use the universal sentence encoder model). When I perform a pipenv lock -r > requirements.txt I get the following required packages:

...

ANSWER

Answered 2020-Jan-09 at 09:54

I have no skills in Django, but it seems that tensorflow is trying to find a package (with a strange name) and failing.

I'd first suggest to try and fix your docker container setup, and check that pipenv lock -r yield the same result inside and outside your container.

1) as you said in the commentaries, on the host pc

Source https://stackoverflow.com/questions/59613957

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

Vulnerabilities

No vulnerabilities reported

Install bert-embedding

You can download it from GitHub.
You can use bert-embedding 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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