Instructions to use Wvolf/ViT_Deepfake_Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wvolf/ViT_Deepfake_Detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Wvolf/ViT_Deepfake_Detection") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Wvolf/ViT_Deepfake_Detection") model = AutoModelForImageClassification.from_pretrained("Wvolf/ViT_Deepfake_Detection") - Inference
- Notebooks
- Google Colab
- Kaggle
This model was trained by Rudolf Enyimba in partial fulfillment of the requirements of Solent University for the degree of MSc Artificial Intelligence and Data Science
This model was trained to detect deepfake images.
The model achieved an accuracy of 98.70% on the test set.
Upload a face image or pick from the samples below to test model accuracy
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