LEBERT | ACL2021 paper `` Lexicon Enhanced Chinese Sequence | Natural Language Processing library
kandi X-RAY | LEBERT Summary
kandi X-RAY | LEBERT Summary
LEBERT is a Python library typically used in Artificial Intelligence, Natural Language Processing, Bert, Transformer applications. LEBERT has no bugs, it has no vulnerabilities and it has low support. However LEBERT build file is not available. You can download it from GitHub.
Code for the ACL2021 paper "Lexicon Enhanced Chinese Sequence Labelling Using BERT Adapter"
Code for the ACL2021 paper "Lexicon Enhanced Chinese Sequence Labelling Using BERT Adapter"
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LEBERT has a low active ecosystem.
It has 286 star(s) with 56 fork(s). There are 6 watchers for this library.
It had no major release in the last 6 months.
There are 1 open issues and 59 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 LEBERT is current.
Quality
LEBERT has no bugs reported.
Security
LEBERT has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
LEBERT does not have a standard license declared.
Check the repository for any license declaration and review the terms closely.
Without a license, all rights are reserved, and you cannot use the library in your applications.
Reuse
LEBERT releases are not available. You will need to build from source code and install.
LEBERT 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.
Top functions reviewed by kandi - BETA
kandi has reviewed LEBERT and discovered the below as its top functions. This is intended to give you an instant insight into LEBERT implemented functionality, and help decide if they suit your requirements.
- Train the model
- Evaluate the model
- Returns a DataLoader for the given dataset
- Compute a sequence of features using a sequence of features
- Performs a forward computation
- Negative log - likelihood loss
- Decode viterbi
- Calculate the PZ
- Given a sentence return a list of matched words
- Insert a word into the tree
- Returns True if word is a word
- Return a list of matched words
- Given a list of vocab_files and a list of vocab_files extract the word from the corpus
- Given a list of corpus files and a list of files return a set of matched words
- Build pretrained embedding for corpus
- Load pretrain embedding
- Inserts a segment vocabulary into the lexicon tree
- Evaluate a model
- Get argparse
- Given a list of files in the lexicon_tree return a set of matched words
- Convert a sentence into distinct words
- Compute the loss function
- Build lexicon tree from vocab_files
- Split a sentence into a list of matched words
- Forward computation
- Convert BMES to JSON
- Set random seed
Get all kandi verified functions for this library.
LEBERT Key Features
No Key Features are available at this moment for LEBERT.
LEBERT Examples and Code Snippets
No Code Snippets are available at this moment for LEBERT.
Community Discussions
Trending Discussions on LEBERT
QUESTION
Gmail changes the color of my text
Asked 2017-Oct-19 at 00:48
ANSWER
Answered 2017-Oct-19 at 00:28You can try updating your code to this. Hopefully, it will help.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install LEBERT
You can download it from GitHub.
You can use LEBERT 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.
You can use LEBERT 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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