Instructions to use prithivMLmods/IndoorOutdoorNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/IndoorOutdoorNet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/IndoorOutdoorNet") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/IndoorOutdoorNet") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/IndoorOutdoorNet") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d41ad2fbd0e6e741cf02bd60d9943f6a4bdeddd55115d40a2cd4d607ce94475e
- Size of remote file:
- 372 MB
- SHA256:
- 8f8f5c4e860c9f0b81a7d6bb0f865d4aaca357ca0ef7a1e7cce48fbacc4e0a28
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