Instructions to use hilmiatha/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hilmiatha/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hilmiatha/image_classification") 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("hilmiatha/image_classification") model = AutoModelForImageClassification.from_pretrained("hilmiatha/image_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 68b0a7b1dc484585a800499379865e0bd6899d2b56acb01b1ef04e728e3511fa
- Size of remote file:
- 343 MB
- SHA256:
- 5204d653f85ea0557c2351656dbe6aee814f1be50d6e69b873c1a3acc4eff278
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