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reginaboateng/
umls_relational_extraction_adapter_PubMedBERT

Name: umls_relational_extraction_adapter_PubMedBERT
Availability: InStock

adapter-transformers

bert

umls

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Adapter `reginaboateng/umls_relational_extraction_adapter_PubMedBERT` for microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext

An adapter for the microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext model that was trained on the umls dataset and includes a prediction head for classification.

This adapter was created for usage with the adapter-transformers library.

Usage

First, install adapter-transformers:

pip install -U adapter-transformers

Note: adapter-transformers is a fork of transformers that acts as a drop-in replacement with adapter support. More

Now, the adapter can be loaded and activated like this:

python

from transformers import AutoAdapterModel

model = AutoAdapterModel.from_pretrained("microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext")
adapter_name = model.load_adapter("reginaboateng/umls_relational_extraction_adapter_PubMedBERT", source="hf", set_active=True)

reginaboateng/
umls_relational_extraction_adapter_PubMedBERT

Adapter `reginaboateng/umls_relational_extraction_adapter_PubMedBERT` for microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext

Usage

Architecture & Training

Evaluation results

Citation

reginaboateng/umls_relational_extraction_adapter_PubMedBERT

Adapter reginaboateng/umls_relational_extraction_adapter_PubMedBERT for microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext

Usage

Architecture & Training

Evaluation results

Citation

reginaboateng/
umls_relational_extraction_adapter_PubMedBERT

Adapter `reginaboateng/umls_relational_extraction_adapter_PubMedBERT` for microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext