Instructions to use ayoubkirouane/Breast-Cancer_SAM_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ayoubkirouane/Breast-Cancer_SAM_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="ayoubkirouane/Breast-Cancer_SAM_v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMaskGeneration processor = AutoProcessor.from_pretrained("ayoubkirouane/Breast-Cancer_SAM_v1") model = AutoModelForMaskGeneration.from_pretrained("ayoubkirouane/Breast-Cancer_SAM_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ayoubkirouane/Breast-Cancer_SAM_v1: direct link, hf CLI and curl.
- Browser
- Download file 375 MB
-
https://huggingface.co/ayoubkirouane/Breast-Cancer_SAM_v1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ayoubkirouane/Breast-Cancer_SAM_v1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ayoubkirouane/Breast-Cancer_SAM_v1/resolve/main/pytorch_model.bin
375 MB
- Xet hash:
- 3c4ec7e7ba98e6b780d9c83cc0c3aab2b2cd5d583d50de24561f38db4f1710c6
- Size of remote file:
- 375 MB
- SHA256:
- 7d2499914fd9b66571b83bb3d97743f7403f2895f1e4b9583afcd238077809b6
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