Instructions to use NeuronZero/SkinCancerClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NeuronZero/SkinCancerClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="NeuronZero/SkinCancerClassifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("NeuronZero/SkinCancerClassifier") model = AutoModelForImageClassification.from_pretrained("NeuronZero/SkinCancerClassifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c38cd3ae5942f9eea91d05c947342fa8425e340c19abbee2746f689d219515a
- Size of remote file:
- 694 MB
- SHA256:
- 8d219e5f8d2177c2040ca23df7cc4be5367b9121fc64c4f0b703cccd12d411d1
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