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 scheduler.pt from DaMsTaR/Detecto-DeepFake_Image_Detector: direct link, hf CLI and curl.
- Browser
- Download file 627 Bytes
-
https://huggingface.co/DaMsTaR/Detecto-DeepFake_Image_Detector/resolve/main/scheduler.pt
- Command line
-
hf download hf://DaMsTaR/Detecto-DeepFake_Image_Detector/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/DaMsTaR/Detecto-DeepFake_Image_Detector/resolve/main/scheduler.pt
627 Bytes
- Xet hash:
- 7a219b061c74b189b8781278ac9aa3e1709eefa8d898b6ab93ef9d87733dcf9c
- Size of remote file:
- 627 Bytes
- SHA256:
- ce7be3828c014df3a8e3ee6df6d1e7b3f7a5de37ca6124b03b9e1583ae0adf63
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