Instructions to use joyc360/deepfakes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joyc360/deepfakes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="joyc360/deepfakes") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("joyc360/deepfakes") model = AutoModelForImageClassification.from_pretrained("joyc360/deepfakes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
deepfakes
Autogenerated by HuggingPics๐ค๐ผ๏ธ
Create your own image classifier for anything by running the demo on Google Colab.
Report any issues with the demo at the github repo.
Example Images
deepfake image
real image
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Evaluation results
- Accuracyself-reported0.816

