Instructions to use Hemg/Acne-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hemg/Acne-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Hemg/Acne-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("Hemg/Acne-classification") model = AutoModelForImageClassification.from_pretrained("Hemg/Acne-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8b5b5f98df5ede51a8c5db63e3a35cf473641e090f63385cb16df4892d59835a
- Size of remote file:
- 4.92 kB
- SHA256:
- 122ecf9b28ca918876f6f56344c596575416d4ebc9c5c2dfc93eebd5e992fd69
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