stacked-ner | BERT models need to be dowloaded

by EMBEDDIA Python Version: Current License: No License

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

kandi X-RAY | stacked-ner Summary

stacked-ner is a Python library. stacked-ner has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

BERT models need to be dowloaded (with the exception of CamemBERT).

Support

Quality

Security

License

Reuse

Support

stacked-ner has a low active ecosystem.

It has 2 star(s) with 0 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of stacked-ner is current.

Quality

stacked-ner has no bugs reported.

Security

stacked-ner has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

stacked-ner 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

stacked-ner 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.

Top functions reviewed by kandi - BETA

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

Main function .
Initialize the model .
Predict on the given data set .
Index data bundle .
Convert tags to IOB2
Performs the forward computation .
Load a csv file .
Convert tags to BIOes
Index datasets .
Process the data bundle .

Get all kandi verified functions for this library.

stacked-ner Key Features

No Key Features are available at this moment for stacked-ner.

stacked-ner Examples and Code Snippets

No Code Snippets are available at this moment for stacked-ner.

Community Discussions

No Community Discussions are available at this moment for stacked-ner.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install stacked-ner

You can download it from GitHub.
You can use stacked-ner 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 .

Find more information at: