Instructions to use DarkVision/Deepfake_detection_image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DarkVision/Deepfake_detection_image with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="DarkVision/Deepfake_detection_image") 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("DarkVision/Deepfake_detection_image") model = AutoModelForImageClassification.from_pretrained("DarkVision/Deepfake_detection_image", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from DarkVision/Deepfake_detection_image: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/DarkVision/Deepfake_detection_image/resolve/main/training_args.bin
- Command line
-
hf download hf://DarkVision/Deepfake_detection_image/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/DarkVision/Deepfake_detection_image/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- 3f6d6e2157ff2798da4f0dd425b1eb554ccf455b4cb16186a284bda76d341766
- Size of remote file:
- 4.03 kB
- SHA256:
- 1e8d19703da0c69d641a6b89f2177e3aec8b1bdf5efdbb94ee8497fc5935ce47
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