Instructions to use dima806/ai_vs_human_generated_image_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/ai_vs_human_generated_image_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dima806/ai_vs_human_generated_image_detection") 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("dima806/ai_vs_human_generated_image_detection") model = AutoModelForImageClassification.from_pretrained("dima806/ai_vs_human_generated_image_detection", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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Verified signaturePredicts with about 97% accuracy whether an attached image is a human made or AI generated. See https://www.kaggle.com/code/dima806/ai-vs-human-generated-images-prediction-vit for more details.  ``` Classification report: precision recall f1-score support human 0.9606 0.9849 0.9726 15990 AI-generated 0.9845 0.9596 0.9719 15990 accuracy 0.9723 31980 macro avg 0.9726 0.9723 0.9723 31980 weighted avg 0.9726 0.9723 0.9723 31980 ```b258c3c -
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