Instructions to use TimKond/diffusion-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TimKond/diffusion-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="TimKond/diffusion-detection") 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("TimKond/diffusion-detection") model = AutoModelForImageClassification.from_pretrained("TimKond/diffusion-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 168 Bytes
1840e63 | 1 2 3 4 5 6 7 | {
"epoch": 3.0,
"train_loss": 0.20243481533847807,
"train_runtime": 2207.1281,
"train_samples_per_second": 24.466,
"train_steps_per_second": 0.765
} |