Instructions to use guinansu/MedSAMix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use guinansu/MedSAMix with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="guinansu/MedSAMix")# Load model directly from transformers import AutoProcessor, AutoModelForMaskGeneration processor = AutoProcessor.from_pretrained("guinansu/MedSAMix") model = AutoModelForMaskGeneration.from_pretrained("guinansu/MedSAMix", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c7adcb91489f01f509190ed5511d7fafedbc79b356a04acd7c89cd48d46c81e
- Size of remote file:
- 375 MB
- SHA256:
- f62015e09cc72696c30973db2d8d873e173c17e11496c8586d21729f543af4d2
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