argilla-io/adept-augmentations
A Python library aimed at dissecting and augmenting NER training data.
This tool helps data scientists and NLP practitioners create more training data for Named Entity Recognition (NER) models, especially when they have very little data to start with. You provide a small set of sentences with labeled entities (like people, locations, or organizations), and it automatically generates many new, diverse sentences by intelligently swapping entities of the same type. The output is an expanded dataset of labeled sentences ready for training your NER model.
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Use this if you are building a Named Entity Recognition model and need to improve its performance, especially when you have a limited amount of labeled training data.
Not ideal if you already have a very large, diverse, and well-performing NER training dataset, or if your task is not Named Entity Recognition.
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Language
Python
License
Apache-2.0
Category
Last pushed
May 11, 2023
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