Instructions to use sgonzalez2000/dermai-efficientnet-b0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sgonzalez2000/dermai-efficientnet-b0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sgonzalez2000/dermai-efficientnet-b0") 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("sgonzalez2000/dermai-efficientnet-b0") model = AutoModelForImageClassification.from_pretrained("sgonzalez2000/dermai-efficientnet-b0") - Notebooks
- Google Colab
- Kaggle
metadata
base_model: google/efficientnet-b0
library_name: transformers
license: apache-2.0
tags:
- image-classification
- skin-lesion
- ham10000
dermai-efficientnet-b0
Fine-tuned google/efficientnet-b0 for 7-class skin lesion classification on HAM10000. Part of the DermAI explainability project comparing CNN and Vision Transformer explanations.