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")# pip install -U transformers accelerate # 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
Download training_args.bin from jkefeli/PrimaryGleasonBERT: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/jkefeli/PrimaryGleasonBERT/resolve/main/training_args.bin
- Command line
-
hf download hf://jkefeli/PrimaryGleasonBERT/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jkefeli/PrimaryGleasonBERT/resolve/main/training_args.bin
3.06 kB
- Xet hash:
- 4bcea442a0e818964797f46ca544c2748e6c4df1cfa19ce44620817cd093d323
- Size of remote file:
- 3.06 kB
- SHA256:
- d137614411c96f2d63f6e41e4d73aad55ac9096f12be9a64c3c27f52d9ef031d
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