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")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMaskGeneration processor = AutoProcessor.from_pretrained("ahishamm/skinsam") model = AutoModelForMaskGeneration.from_pretrained("ahishamm/skinsam", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ahishamm/skinsam: direct link, hf CLI and curl.
- Browser
- Download file 375 MB
-
https://huggingface.co/ahishamm/skinsam/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://ahishamm/skinsam@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ahishamm/skinsam/resolve/refs%2Fpr%2F1/pytorch_model.bin
375 MB
- Xet hash:
- d786a8c191b73a39cdcd90bffe8859a100e4957dd97eed7b1e7e65b97b2b8238
- Size of remote file:
- 375 MB
- SHA256:
- 105c19b199da68a466ac7a6dd397244618c4694c1d0fc5cf24f0724bb225581a
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