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 rng_state.pth from DaMsTaR/Detecto-DeepFake_Image_Detector: direct link, hf CLI and curl.
- Browser
- Download file 14.6 kB
-
https://huggingface.co/DaMsTaR/Detecto-DeepFake_Image_Detector/resolve/main/rng_state.pth
- Command line
-
hf download hf://DaMsTaR/Detecto-DeepFake_Image_Detector/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/DaMsTaR/Detecto-DeepFake_Image_Detector/resolve/main/rng_state.pth
14.6 kB
- Xet hash:
- f1c1a8ddec3a4778024b3196904190a4b3df519a8ddddb3dd343fa1bf41772b8
- Size of remote file:
- 14.6 kB
- SHA256:
- 3598bb66508fcbfcbe2266f54444cec8ec54cd97104468acb81b387e899c9e7e
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