Instructions to use rwood-97/sam_os_contours with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rwood-97/sam_os_contours with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="rwood-97/sam_os_contours")# Load model directly from transformers import AutoProcessor, AutoModelForMaskGeneration processor = AutoProcessor.from_pretrained("rwood-97/sam_os_contours") model = AutoModelForMaskGeneration.from_pretrained("rwood-97/sam_os_contours") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c361aa0770242e907c05cc5dab6ee2b888aedd7839b09209426e0ba65c6abfb4
- Size of remote file:
- 375 MB
- SHA256:
- b2b7074cb1adb6437fed3af5784d89d947cfec79c9522750bf05efdacb26e62c
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