Trainable components overview
In addition to its rule-based pipeline components, EDS-NLP offers new trainable components to fit and run machine learning models for classic biomedical information extraction tasks.
All trainable components implement the TorchComponent
class, which provides a common API for training and inference.
Available components :
Name | Description |
---|---|
eds.transformer | Embed text with a transformer model |
eds.text_cnn | Contextualize embeddings with a CNN |
eds.span_pooler | A span embedding component that aggregates word embeddings |
eds.ner_crf | A trainable component to extract entities |
eds.extractive_qa | A trainable component for extractive question answering |
eds.span_classifier | A trainable component for multi-class multi-label span classification |
eds.span_linker | A trainable entity linker (i.e. to a list of concepts) |
eds.biaffine_dep_parser | A trainable biaffine dependency parser |