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compacter_umls_relational_extraction_adapter_BERT
reginaboateng/compacter_umls_relational_extraction_adapter_BERT
compacter_umls_relational_extraction_adapter_BERT is a machine learning model from reginaboateng. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for adapter-transformers.
An adapter for the bert-base-uncased model that was trained on the umls dataset and includes a prediction head for classification.
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At a glance
- Library
- adapter-transformers
- Access
- Public
- Created
- Aug 23, 2023
- Updated
- Aug 23, 2023
- SHA
- 88eeea6b
Datasets
Model card
From the Hugging Face model README
Adapter reginaboateng/compacter_umls_relational_extraction_adapter_BERT for bert-base-uncased
An adapter for the bert-base-uncased 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:
from transformers import AutoAdapterModel
model = AutoAdapterModel.from_pretrained("bert-base-uncased")
adapter_name = model.load_adapter("reginaboateng/compacter_umls_relational_extraction_adapter_BERT", source="hf", set_active=True)
Architecture & Training
<!-- Add some description here -->Evaluation results
<!-- Add some description here -->Citation
<!-- Add some description here -->- Library
- adapter-transformers
- Created
- Aug 23, 2023
- Updated
- Aug 23, 2023