Instructions to use kaesve/BioBERT_patent_reference_extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kaesve/BioBERT_patent_reference_extraction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="kaesve/BioBERT_patent_reference_extraction")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("kaesve/BioBERT_patent_reference_extraction") model = AutoModelForMaskedLM.from_pretrained("kaesve/BioBERT_patent_reference_extraction") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 586953aa0c3c7b620ed4608bf9ef02645ba0f39537323a64875f616883298dde
- Size of remote file:
- 433 MB
- SHA256:
- 3a8a1869efdda0492b82d3dac04b1809d8a9d7091749143376dfad19791a494b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.