Downloads · 30 days
1
6% of all-time downloads
pfeiffer_PubmedBert_adapter_ner_pico_for_classification_task
reginaboateng/pfeiffer_PubmedBert_adapter_ner_pico_for_classification_task
pfeiffer_PubmedBert_adapter_ner_pico_for_classification_task 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 microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext model that was trained on the piconer dataset.
All-time downloads
16
Public
Repo size
3.6 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin3.6 MB · 100%
At a glance
- Library
- adapter-transformers
- Access
- Public
- Created
- Aug 8, 2023
- Updated
- Aug 8, 2023
- SHA
- 709506e6
Model card
From the Hugging Face model README
Adapter reginaboateng/pfeiffer_PubmedBert_adapter_ner_pico_for_classification_task 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 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("microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext")
adapter_name = model.load_adapter("reginaboateng/pfeiffer_PubmedBert_adapter_ner_pico_for_classification_task", 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 8, 2023
- Updated
- Aug 8, 2023