Instructions to use Onno/hotels_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Onno/hotels_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Onno/hotels_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("Onno/hotels_classifier") model = AutoModelForImageClassification.from_pretrained("Onno/hotels_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0dee9e98765d4a35744ba4316d8bb75dda92c782f0fa8e4c980246da180defc5
- Size of remote file:
- 343 MB
- SHA256:
- 3436130d81d25adac7e1f69f09a8a8c4fd11efa0c6c368b7e084ab704cfa022e
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