Instructions to use RohanVB/umlsbert_ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RohanVB/umlsbert_ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="RohanVB/umlsbert_ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("RohanVB/umlsbert_ner") model = AutoModelForTokenClassification.from_pretrained("RohanVB/umlsbert_ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 82b0fcbb3bd85f94f169effc2f189ff9ef7a94e739638404b6959d614ae61efb
- Size of remote file:
- 433 MB
- SHA256:
- 543c5b6000a9e094ebeb8422acb21ea5d4ef2689fe1a9c5db797d49a196b98ae
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.