Instructions to use havocy28/VetBERTDx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use havocy28/VetBERTDx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="havocy28/VetBERTDx")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("havocy28/VetBERTDx") model = AutoModelForSequenceClassification.from_pretrained("havocy28/VetBERTDx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c54fec20a9944e4207a1cdee59715c85ea03d23954b66ad6f1a8898c0549d26
- Size of remote file:
- 433 MB
- SHA256:
- e88b3d06652975f82f4e6c609cdb10cab61dc6525fc78c9f01b53cf06a60d134
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