Instructions to use JuanMa360/room-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JuanMa360/room-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="JuanMa360/room-classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("JuanMa360/room-classification") model = AutoModelForImageClassification.from_pretrained("JuanMa360/room-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download images/Exterior.jpeg from JuanMa360/room-classification: direct link, hf CLI and curl.
- Browser
- Download file 244 kB
-
https://huggingface.co/JuanMa360/room-classification/resolve/main/images/Exterior.jpeg
- Command line
-
hf download hf://JuanMa360/room-classification/images/Exterior.jpeg
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curl -L -o Exterior.jpeg https://huggingface.co/JuanMa360/room-classification/resolve/main/images/Exterior.jpeg
244 kB

- Xet hash:
- a0feb739f95388ef6d6101ca18e64252a34be3fed775c8a757d0bec2b848350b
- Size of remote file:
- 244 kB
- SHA256:
- faeb967d47e6df08f97c328a677ef9ccba78cda5964eaf0b83880e2357c0bb4f
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