pyvandenbussche/transformers-ner
Experiment on NER task using Huggingface state-of-the-art Transformers Natural Language Models library
This is a developer's experimental project for named entity recognition (NER). It takes raw text data, such as scientific papers or articles, and processes it to identify and categorize key entities like chemical compounds or diseases. This tool is designed for natural language processing engineers or researchers who need to experiment with and evaluate different pre-trained transformer models for NER tasks.
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Use this if you are a developer looking to run and compare state-of-the-art transformer models (BERT, SciBERT, SpanBERT) for named entity recognition on your own text datasets.
Not ideal if you are a non-technical user looking for an out-of-the-box solution or a simple API to perform NER without writing code.
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Python
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MIT
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Last pushed
Jul 22, 2023
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