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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ec417bf806e9761618f345587fd28e850df190919018a7e4fbd812aca7e34db
- Size of remote file:
- 348 MB
- SHA256:
- eada057239c274dcf90bacfeb17d0c3298dfa3d6f214a26f3a3ca8d2d592f9e5
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