Instructions to use gdario/biobert_bioasq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gdario/biobert_bioasq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="gdario/biobert_bioasq")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("gdario/biobert_bioasq") model = AutoModelForQuestionAnswering.from_pretrained("gdario/biobert_bioasq") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9376a042d59f8e6ab1162eadbaa6c6257efe08633f50bf7c63276b6f00f7cfdc
- Size of remote file:
- 431 MB
- SHA256:
- b265379233f055e36d229fdf5fe62df73dc3a1b07fc0c130dcd67ac691bab9a7
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.