NERDA | tuning pretrained transformers for Named-Entity Recognition | Natural Language Processing library

by ebanalyse Python Version: 1.0.0 License: MIT

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

kandi X-RAY | NERDA Summary

NERDA is a Python library typically used in Artificial Intelligence, Natural Language Processing, Deep Learning, Pytorch, Bert, Neural Network, Transformer applications. NERDA has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install NERDA' or download it from GitHub, PyPI.

Not only is NERDA a mesmerizing muppet-like character. NERDA is also a python package, that offers a slick easy-to-use interface for fine-tuning pretrained transformers for Named Entity Recognition (=NER) tasks. You can also utilize NERDA to access a selection of precooked NERDA models, that you can use right off the shelf for NER tasks. NERDA is built on huggingface transformers and the popular pytorch framework.

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Quality

Security

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Support

NERDA has a low active ecosystem.

It has 146 star(s) with 34 fork(s). There are 9 watchers for this library.

It had no major release in the last 12 months.

There are 13 open issues and 19 have been closed. On average issues are closed in 46 days. There are 7 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of NERDA is 1.0.0

Quality

NERDA has 0 bugs and 0 code smells.

Security

NERDA has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

NERDA code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

NERDA is licensed under the MIT License. This license is Permissive.

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

Reuse

NERDA releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

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

Installation instructions, examples and code snippets are available.

It has 977 lines of code, 64 functions and 20 files.

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

Top functions reviewed by kandi - BETA

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

Compute the performance of the entity
Predict from sentences
Predict on sentences
Create a data loader
Compute the objective function
Train the model
Get the Dane data for a given split
Train a model
Download pane data
Download and extract an archive
Predict the text
Predict the given text
Forward computation
Return a dictionary mapping keyword arguments to keyword arguments
Deploy a model to S3
Download data from deepai
Get the Dane data

Get all kandi verified functions for this library.

NERDA Key Features

No Key Features are available at this moment for NERDA.

NERDA Examples and Code Snippets

No Code Snippets are available at this moment for NERDA.

Community Discussions

Trending Discussions on NERDA

ValueError with NERDA model import

QUESTION

ValueError with NERDA model import

Asked 2021-Jun-08 at 21:38

I'm trying to import the NERDA library in order use it to engage in a Named-Entity Recognition task in Python. I initially tried importing the library in a jupyter notebook and got the following error:

...

ANSWER

Answered 2021-Jun-08 at 21:38

Take a look at the source code of the used huggingface_hub lib. They comparing the version of your python version to do different imports.
But you uses a release candidate python version (this tells the value '6rc1', that caused the error). Because they didn't expect/handle this, you get the int-parse-ValueError.

Solution 1:
Update your python version to a stable version. No release candidate. So you have an int-only version number.

Solution 2:
Monkeypatch sys.version, before you import the NERDA libs.

Source https://stackoverflow.com/questions/67894649

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