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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a577fff793f527070cc3c1f06a2e721273577e7531c1cc4a486eb74d65cbd689
- Size of remote file:
- 5.11 kB
- SHA256:
- c98008ad3e4d73397d6a87b9bfe2dce0b4affc6b9ecff2db964d975314a67c81
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