Instructions to use pucpr/clinicalnerpt-disease with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pucpr/clinicalnerpt-disease with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="pucpr/clinicalnerpt-disease")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("pucpr/clinicalnerpt-disease") model = AutoModelForTokenClassification.from_pretrained("pucpr/clinicalnerpt-disease", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b4123ae15cc8c6158167ed6b4141da00b24d1b09bad365a34d9e1472c535f25b
- Size of remote file:
- 709 MB
- SHA256:
- 8fa3630402dea4930754b890f9ac022201a9c0c7ad3b49d3a0bb2c436dbbdb50
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