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:
- 7fb682ca5a1cd20895f284c51661cbb20faf0062e99a1521719fdd0d8e73a827
- Size of remote file:
- 4.22 kB
- SHA256:
- a3700f9d6f06cbcbec3ff8781850f7ab229c8d65a448a0e6ccf238fd99b4733b
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