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")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/IndoorOutdoorNet") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/IndoorOutdoorNet", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-1250/optimizer.pt from prithivMLmods/IndoorOutdoorNet: direct link, hf CLI and curl.
- Browser
- Download file 687 MB
-
https://huggingface.co/prithivMLmods/IndoorOutdoorNet/resolve/main/checkpoint-1250/optimizer.pt
- Command line
-
hf download hf://prithivMLmods/IndoorOutdoorNet/checkpoint-1250/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/prithivMLmods/IndoorOutdoorNet/resolve/main/checkpoint-1250/optimizer.pt
687 MB
- Xet hash:
- b0349e9c19eb2841d76144cc4b13fabdec06f1ce1df2bc4d886cd46f9d115583
- Size of remote file:
- 687 MB
- SHA256:
- 99b09af1af5a6d1ce8139d5a158b1fdb2937609af5448ff7172d67a58f8bb3b5
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