Instructions to use HPAI-BSC/SuSy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HPAI-BSC/SuSy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="HPAI-BSC/SuSy") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("HPAI-BSC/SuSy", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add susy dataset and metric
Browse files
README.md
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- ehristoforu/midjourney-images
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- nateraw/midjourney-texttoimage
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- duchaiten/duchaiten-realistic-sdxl
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tags:
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- vision
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- image-classification
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- synthetic content detection
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pipeline_tag: image-classification
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---
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# SuSy - Synthetic Image Detector
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- ehristoforu/midjourney-images
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- nateraw/midjourney-texttoimage
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- duchaiten/duchaiten-realistic-sdxl
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- HPAI-BSC/SuSy-Dataset
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tags:
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- vision
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- image-classification
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- synthetic content detection
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pipeline_tag: image-classification
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metrics:
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- recall
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---
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# SuSy - Synthetic Image Detector
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