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
Commit History
-
Adding `safetensors` variant of this model
Verified signatureThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.6934f44
-
Update README.md
32255d4 -
Update README.md
48771eb -
Create README.md
26f7f25 -
Upload config.json
f886c5a -
Upload pytorch_model.bin
2007b6a -
Upload trainer_state.json
dd92e3a -
Upload training_args.bin
7e685d3 -
initial commit
544e1a3