Instructions to use medkit/DrBERT-CASM2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use medkit/DrBERT-CASM2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="medkit/DrBERT-CASM2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("medkit/DrBERT-CASM2") model = AutoModelForTokenClassification.from_pretrained("medkit/DrBERT-CASM2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a04d6ba3e7ad6819df4396c36ce3aafb17c00752e6a5d1e360199face6098620
- Size of remote file:
- 436 MB
- SHA256:
- 3526e3c39fd476e1004854f34ad46f2088a51998aff0d7a25aa9e2f25c6c3146
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