Instructions to use flaviagiammarino/medsam-vit-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flaviagiammarino/medsam-vit-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="flaviagiammarino/medsam-vit-base")# Load model directly from transformers import AutoProcessor, AutoModelForMaskGeneration processor = AutoProcessor.from_pretrained("flaviagiammarino/medsam-vit-base") model = AutoModelForMaskGeneration.from_pretrained("flaviagiammarino/medsam-vit-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 28801dbc2e66c5d7cdf2675bcf43f3aaa720bd557307b7e64c78c883fa2374cb
- Size of remote file:
- 375 MB
- SHA256:
- b80a96478503f89e76f1f7bbba50cfcd4ec9e7467f0d5185310216b33946ec9c
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