Instructions to use ongkn/attraction-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ongkn/attraction-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ongkn/attraction-classifier") 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("ongkn/attraction-classifier") model = AutoModelForImageClassification.from_pretrained("ongkn/attraction-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed0d3d3985869c26dd9e603ba500716558fe129ea4b5dbfaacdbd6d41fdd9890
- Size of remote file:
- 4.03 kB
- SHA256:
- aae4dfc02bfa4bbc3ffe98fd424a62a7b32e21fa2b07797f67b55cf2bdde3de9
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