Instructions to use jkefeli/PrimaryGleasonBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jkefeli/PrimaryGleasonBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jkefeli/PrimaryGleasonBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jkefeli/PrimaryGleasonBERT") model = AutoModelForSequenceClassification.from_pretrained("jkefeli/PrimaryGleasonBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b3f0d474da4746183e0001d9c9d099eeb44cd8728c74de4f598136abfceac5d
- Size of remote file:
- 433 MB
- SHA256:
- bb4a708fc26dd48437bca84b6039c559235ca42d9ad85706a71b5881099222da
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