Instructions to use havocy28/VetBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use havocy28/VetBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="havocy28/VetBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("havocy28/VetBERT") model = AutoModelForPreTraining.from_pretrained("havocy28/VetBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 141d0e81797f72ee7ab0f7e1840086677f63448af52c362a3640bbca5cc32044
- Size of remote file:
- 436 MB
- SHA256:
- cd9479168b492efd8f48ea20ed221362c78a3bbe18a7bc47ae374e277b63f8b8
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