Instructions to use Cardio123/medroberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cardio123/medroberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Cardio123/medroberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Cardio123/medroberta-base") model = AutoModelForMaskedLM.from_pretrained("Cardio123/medroberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1dc0ffebeace63f94a1548e845c8d2928bec6e96d4e3ba045df6cfe42d033969
- Size of remote file:
- 498 MB
- SHA256:
- 4230208279b7f972774a0f42a77baf86409611e4755bd10bc5e65e475551bf6f
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