Instructions to use facebook/sam-vit-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/sam-vit-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="facebook/sam-vit-base")# Load model directly from transformers import AutoProcessor, AutoModelForMaskGeneration processor = AutoProcessor.from_pretrained("facebook/sam-vit-base") model = AutoModelForMaskGeneration.from_pretrained("facebook/sam-vit-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4bca31314fefc76ae7c8675d0cbb709608bd5093cc1ab3446b8a8836a981554f
- Size of remote file:
- 375 MB
- SHA256:
- 1a1e860feeb895bc46f704d4faad2a0be739b5dfdca0ebdda520ffbcfb73f348
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