Instructions to use reginaboateng/BioBERT_adapter_ner_pico_for_classification_task with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use reginaboateng/BioBERT_adapter_ner_pico_for_classification_task with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("dmis-lab/biobert-v1.1") model.load_adapter("reginaboateng/BioBERT_adapter_ner_pico_for_classification_task", set_active=True) - Notebooks
- Google Colab
- Kaggle
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Download README.md from reginaboateng/BioBERT_adapter_ner_pico_for_classification_task: direct link, hf CLI and curl.
- Browser
- Download file 1.25 kB
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https://huggingface.co/reginaboateng/BioBERT_adapter_ner_pico_for_classification_task/resolve/main/README.md
- Command line
-
hf download hf://reginaboateng/BioBERT_adapter_ner_pico_for_classification_task/README.md
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curl -L -o README.md https://huggingface.co/reginaboateng/BioBERT_adapter_ner_pico_for_classification_task/resolve/main/README.md
1.25 kB
metadata
tags:
- bert
- adapter-transformers
- adapterhub:pico_ner
datasets:
- reginaboateng/cleaned_ebmnlp_pico
Adapter reginaboateng/BioBERT_adapter_ner_pico_for_classification_task for dmis-lab/biobert-v1.1
An adapter for the dmis-lab/biobert-v1.1 model that was trained on the pico_ner dataset.
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("dmis-lab/biobert-v1.1")
adapter_name = model.load_adapter("reginaboateng/BioBERT_adapter_ner_pico_for_classification_task", source="hf", set_active=True)