fine-tune transformer-based language models for named entity recognition
Project description
A python package to fine-tune transformer-based language models for named entity recognition (NER).
Resources
Source Code: https://github.com/flxst/nerblackbox
Documentation: https://flxst.github.io/nerblackbox
About
Transformer-based language models like BERT have had a game-changing impact on Natural Language Processing.
In order to utilize Hugging Face’s publicly accessible pretrained models for Named Entity Recognition, one needs to retrain (or “fine-tune”) them using labeled text.
nerblackbox makes this easy.
You give it
a Dataset (labeled text)
a Pretrained Model (transformers)
and you get
the best Fine-tuned Model
its Performance on the dataset
Installation
pip install nerblackbox
Usage
see documentation: https://flxst.github.io/nerblackbox
Citation
@misc{nerblackbox,
author = {Stollenwerk, Felix},
title = {nerblackbox: a python package to fine-tune transformer-based language models for named entity recognition},
year = {2021},
url = {https://github.com/flxst/nerblackbox},
}
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