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
Download pytorch_adapter.bin from reginaboateng/BioBERT_adapter_ner_pico_for_classification_task: direct link, hf CLI and curl.
- Browser
- Download file 7.19 MB
-
https://huggingface.co/reginaboateng/BioBERT_adapter_ner_pico_for_classification_task/resolve/main/pytorch_adapter.bin
- Command line
-
hf download hf://reginaboateng/BioBERT_adapter_ner_pico_for_classification_task/pytorch_adapter.bin
-
curl -L -o pytorch_adapter.bin https://huggingface.co/reginaboateng/BioBERT_adapter_ner_pico_for_classification_task/resolve/main/pytorch_adapter.bin
7.19 MB
- Xet hash:
- 3d7964894987e8349c23ecc8ce69dd99fb65fb6678f662fc72ec1c6664c16a95
- Size of remote file:
- 7.19 MB
- SHA256:
- 628e8b1514332fc6d131f8b1136507f8413aaa0a9136833866320a1a9523717c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.