Instructions to use ardha27/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ardha27/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ardha27/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("ardha27/image_classification") model = AutoModelForImageClassification.from_pretrained("ardha27/image_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3e0106490ae238f9855edcadf99c80ac8c3d172bed310a98ecc0bbda4cbf6917
- Size of remote file:
- 4.6 kB
- SHA256:
- a74dbdce07ed9fab1f05585832615ede50d030d26035291160ed1ffc93309762
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