Instructions to use ThankGod/efficientnet-b7-vit-finetuned-melanoma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThankGod/efficientnet-b7-vit-finetuned-melanoma with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ThankGod/efficientnet-b7-vit-finetuned-melanoma") 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("ThankGod/efficientnet-b7-vit-finetuned-melanoma") model = AutoModelForImageClassification.from_pretrained("ThankGod/efficientnet-b7-vit-finetuned-melanoma") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a9cf9de4ac6ce4fd990c13ff5b98f7ba8479958cbd27f63836ea2ec473850c5d
- Size of remote file:
- 257 MB
- SHA256:
- 24bb887399c88001bc94156e116023bd7f995142af3561cff822abab3466a65a
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