Instructions to use SeyedAli/Melanoma-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SeyedAli/Melanoma-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="SeyedAli/Melanoma-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("SeyedAli/Melanoma-Classification") model = AutoModelForImageClassification.from_pretrained("SeyedAli/Melanoma-Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 202 Bytes
f99dc78 | 1 2 3 4 5 6 7 8 | {
"epoch": 4.0,
"eval_accuracy": 0.8166567988948096,
"eval_loss": 0.5749832987785339,
"eval_runtime": 91.2537,
"eval_samples_per_second": 55.527,
"eval_steps_per_second": 6.948
} |