Instructions to use prithivMLmods/AI-vs-Deepfake-vs-Real with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/AI-vs-Deepfake-vs-Real with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/AI-vs-Deepfake-vs-Real") 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/AI-vs-Deepfake-vs-Real") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/AI-vs-Deepfake-vs-Real") - Notebooks
- Google Colab
- Kaggle
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# **AI-vs-Deepfake-vs-Real**
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AI-vs-Deepfake-vs-Real is an image classification model for differentiating between artificial, deepfake, and real images. It is based on Google's ViT model (`google/vit-base-patch32-224-in21k`).
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# **Inference with Hugging Face Pipeline**
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```python
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from transformers import pipeline
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# **AI-vs-Deepfake-vs-Real**
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AI-vs-Deepfake-vs-Real is an image classification model for differentiating between artificial, deepfake, and real images. It is based on Google's ViT model (`google/vit-base-patch32-224-in21k`).
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# **Inference with Hugging Face Pipeline**
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```python
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from transformers import pipeline
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