Instructions to use ahishamm/skinsam with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahishamm/skinsam with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("mask-generation", model="ahishamm/skinsam")# Load model directly from transformers import AutoProcessor, AutoModelForMaskGeneration processor = AutoProcessor.from_pretrained("ahishamm/skinsam") model = AutoModelForMaskGeneration.from_pretrained("ahishamm/skinsam") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d786a8c191b73a39cdcd90bffe8859a100e4957dd97eed7b1e7e65b97b2b8238
- Size of remote file:
- 375 MB
- SHA256:
- 105c19b199da68a466ac7a6dd397244618c4694c1d0fc5cf24f0724bb225581a
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