Instructions to use hchcsuim/FaceAIorNot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hchcsuim/FaceAIorNot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hchcsuim/FaceAIorNot") 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("hchcsuim/FaceAIorNot") model = AutoModelForImageClassification.from_pretrained("hchcsuim/FaceAIorNot") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5541b3ba60b4b85bd581c54bff506693900dcff4e579121bfe1724382e6f8a51
- Size of remote file:
- 110 MB
- SHA256:
- 8772014e4ebe4567710cb45a23e3c2eec0b912b12a800c21939dbcd388b8a53b
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