v2.3.0

2.3.0 - 2024-12-17

Features

• Release new multilabel biomedBERT model trained on LLM (Gemini) synthetically generated NER data. The model was trained on over 7000 LLM annoted documents with a total of 295822 samples.
  The model was trained for 21 epochs and achieved an F1 score of 95.6% on a held out test set. (multilabel_bert)
• added multilabel NER training example and config.
• added scaling kazu with Ray docs and example.

Bugfixes

• Fix issue with TransformersModelForTokenClassificationNerStep when processing large amounts of documents. The fix offloads tensors onto cpu before performin the torch.cat operation which lead to a zero tensor before. (pytorch_memory_issue)