Instructions to use prithivMLmods/Deepfake-Real-Class-Siglip2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Deepfake-Real-Class-Siglip2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Deepfake-Real-Class-Siglip2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/Deepfake-Real-Class-Siglip2") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Deepfake-Real-Class-Siglip2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5ef775b94b2c42ab973f82374d5e348687966b6b4d6fe89e17bc87c9dec5bdf5
- Size of remote file:
- 687 MB
- SHA256:
- d7d8d055798564c2ffc2bb673186cba0e7ddb7f0c261b670568dd9404cc38cab
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