Instructions to use DaMsTaR/Detecto-DeepFake_Image_Detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DaMsTaR/Detecto-DeepFake_Image_Detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="DaMsTaR/Detecto-DeepFake_Image_Detector") 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("DaMsTaR/Detecto-DeepFake_Image_Detector") model = AutoModelForImageClassification.from_pretrained("DaMsTaR/Detecto-DeepFake_Image_Detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from DaMsTaR/Detecto-DeepFake_Image_Detector: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/DaMsTaR/Detecto-DeepFake_Image_Detector/resolve/main/model.safetensors
- Command line
-
hf download hf://DaMsTaR/Detecto-DeepFake_Image_Detector/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/DaMsTaR/Detecto-DeepFake_Image_Detector/resolve/main/model.safetensors
343 MB
- Xet hash:
- 40342c4e2519821cf9cf416fb6caad7633175ca3faf43b12e11b525d5cba0305
- Size of remote file:
- 343 MB
- SHA256:
- 4f6bdc992eb16a390aa0bf07d643c938458406684a1894619871548da6e456d5
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