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:
- 139aece41c5dc8fd5c32a21b40b4fcf8ddac3a65bbe19fb6c73a63af28138012
- Size of remote file:
- 343 MB
- SHA256:
- 92d109f6fcbf1e8ae513fc0f85b4d6208ae7cd0f2273dc43fda69b91e2099af3
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