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")# 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
- Xet hash:
- 877154e5def0b6bd01a99790530bfe6d691be9a60c35041f2b6074c235e042d2
- Size of remote file:
- 5.3 kB
- SHA256:
- 98a58791d1445928df8775da8fea14195f443d87f2ecf20bccfef5db1511bf1a
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