Instructions to use umm-maybe/AI-image-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use umm-maybe/AI-image-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="umm-maybe/AI-image-detector") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("umm-maybe/AI-image-detector", dtype="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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license: cc-by-4.0
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*__NOTE__: Unless you are trying to detect imagery generated using older models such as VQGAN, please use the [updated version](https://huggingface.co/Organika/sdxl-detector) of this detector instead.*
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This model is a proof-of-concept demonstration of using a ViT model to predict whether an artistic image was generated using AI.
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license: cc-by-4.0
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*__NOTE__: Unless you are trying to detect imagery generated using older models such as VQGAN+CLIP, please use the [updated version](https://huggingface.co/Organika/sdxl-detector) of this detector instead.*
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This model is a proof-of-concept demonstration of using a ViT model to predict whether an artistic image was generated using AI.
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