Image Classification
Transformers
Safetensors
vit
deep-fake
ViT
detection
Image
transformers-4.49.0.dev0
precision-92.12
v2
Instructions to use prithivMLmods/Deep-Fake-Detector-v2-Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Deep-Fake-Detector-v2-Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Deep-Fake-Detector-v2-Model") 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("prithivMLmods/Deep-Fake-Detector-v2-Model") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Deep-Fake-Detector-v2-Model") - Inference
- Notebooks
- Google Colab
- Kaggle
Create README.md
Browse files
README.md
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```
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Classification report:
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precision recall f1-score support
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Realism 0.9683 0.8708 0.9170 28001
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Deepfake 0.8826 0.9715 0.9249 28000
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accuracy 0.9212 56001
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macro avg 0.9255 0.9212 0.9210 56001
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weighted avg 0.9255 0.9212 0.9210 56001
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```
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