Instructions to use Anwarkh1/Skin_Cancer-Image_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Anwarkh1/Skin_Cancer-Image_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Anwarkh1/Skin_Cancer-Image_Classification") 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("Anwarkh1/Skin_Cancer-Image_Classification") model = AutoModelForImageClassification.from_pretrained("Anwarkh1/Skin_Cancer-Image_Classification") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa3246a96c908b2be342ae0121f3a273d6b1bbc4a834ed92fc105178b472d43c
- Size of remote file:
- 343 MB
- SHA256:
- b8136bbbdd085cc97f69bdef01bd0c4c54262cf3ba44f5a94ebc9c8c54e85d60
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