Metadata-Version: 2.1
Name: nerblackbox
Version: 0.0.11
Summary: fine-tune transformer-based language models for named entity recognition
Home-page: https://pypi.org/project/nerblackbox
Author: Felix Stollenwerk
Author-email: felix.stollenwerk@arbetsformedlingen.se
License: Apache 2.0
Description: ===========
        nerblackbox
        ===========
        
        A python package to fine-tune transformer-based language models for named entity recognition (NER).
        
        .. image:: https://img.shields.io/pypi/v/nerblackbox
            :target: https://pypi.org/project/nerblackbox
            :alt: PyPI
        
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            :alt: PyPI - Python Version
        
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            :target: https://travis-ci.com/github/af-ai-center/nerblackbox
            :alt: Travis CI
        
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            :target: https://coveralls.io/github/af-ai-center/nerblackbox?branch=master
        
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            :target: https://github.com/psf/black
        
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            :target: https://github.com/af-ai-center/nerblackbox/blob/latest/LICENSE.txt
            :alt: PyPI - License
        
        Resources
        =========
        
        - Source Code: https://github.com/af-ai-center/nerblackbox
        - Documentation: https://af-ai-center.github.io/nerblackbox
        - PyPI: https://pypi.org/project/nerblackbox
        
        About
        =====
        
        `Transformer-based language models <https://arxiv.org/abs/1706.03762>`_ like `BERT <https://arxiv.org/abs/1810.04805>`_ have had a `game-changing impact <https://paperswithcode.com/task/language-modelling>`_ on Natural Language Processing.
        
        In order to utilize `Hugging Face's publicly accessible pretrained models <https://huggingface.co/transformers/pretrained_models.html>`_ for
        `Named Entity Recognition <https://en.wikipedia.org/wiki/Named-entity_recognition>`_,
        one needs to retrain (or "fine-tune") them using labeled text.
        
        **nerblackbox makes this easy.**
        
        .. image:: https://raw.githubusercontent.com/af-ai-center/nerblackbox/master/docs/docs/images/nerblackbox.png
        
        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://af-ai-center.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/af-ai-center/nerblackbox},
            }
        
Keywords: NLP,NER,named entity recognition,BERT,transformer,pytorch
Platform: UNKNOWN
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Operating System :: Unix
Classifier: Topic :: Text Processing :: Linguistic
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
Provides-Extra: dev
