Instructions to use alessandroseni/room-type-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alessandroseni/room-type-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="alessandroseni/room-type-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("alessandroseni/room-type-detection") model = AutoModelForImageClassification.from_pretrained("alessandroseni/room-type-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bcb64e76533b83e87bcd2ad7db0a44083a65505569933ec5f8fb620b6ac3f45f
- Size of remote file:
- 343 MB
- SHA256:
- a8ebfd2a224b3853e49aa249bb08707d4e3a14e6a5fc9212a1de5c6c7f812cd6
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