Instructions to use drab/Infrastructures with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use drab/Infrastructures with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="drab/Infrastructures") 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("drab/Infrastructures") model = AutoModelForImageClassification.from_pretrained("drab/Infrastructures") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 513531911eef6265a557db8f51395eed5bd230fbfc55c8486a50ea18abd517e7
- Size of remote file:
- 343 MB
- SHA256:
- 7f3bad28d7d23e2357c0c5c995480f58bd229cea6398b8892cbf0bfa06610d50
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