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 optimizer.pt from DarkVision/Deepfake_detection_image: direct link, hf CLI and curl.
- Browser
- Download file 687 MB
-
https://huggingface.co/DarkVision/Deepfake_detection_image/resolve/main/optimizer.pt
- Command line
-
hf download hf://DarkVision/Deepfake_detection_image/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/DarkVision/Deepfake_detection_image/resolve/main/optimizer.pt
687 MB
- Xet hash:
- 9746e154f2629ce409c27adaf607dedc122f426244a451a8f93070d6370ad0d7
- Size of remote file:
- 687 MB
- SHA256:
- b6e607a4af12ed0c24ffa7f37196241b56136a4f91c3ff8a7856ce31e86b43af
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