Instructions to use ParamDev/clinicalbert-medical-doc-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ParamDev/clinicalbert-medical-doc-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ParamDev/clinicalbert-medical-doc-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ParamDev/clinicalbert-medical-doc-classifier") model = AutoModelForSequenceClassification.from_pretrained("ParamDev/clinicalbert-medical-doc-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 25ccb73a4c5114ad9e42b26ad3e2c107b3e2260f18295170ae4f14fa400bb9d5
- Size of remote file:
- 433 MB
- SHA256:
- c0493807377cee396a1e429584e0bb2a4d3e25c08bdfdb3f4621cc0bce96e960
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