Instructions to use flatmoon102/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flatmoon102/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="flatmoon102/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("flatmoon102/image_classification") model = AutoModelForImageClassification.from_pretrained("flatmoon102/image_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8b2e22bb6f74800d67e4c9d5cdeec27ed086929c754b9e730ed2ad7320f6c528
- Size of remote file:
- 343 MB
- SHA256:
- 29f0cd5225f559ea386df434bdc4c3de35626bec9f8f6ae255568c20a13e5dae
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