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:
- 88619c77b74cdba656d49798d90de03e84dc055b0820678062903d5b887bb404
- Size of remote file:
- 343 MB
- SHA256:
- 95532d623a8fcb61c7cf546fbf8b654bcd93c4002cc8d288f2adcd701a1a48bc
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