Instructions to use kensvin/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kensvin/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="kensvin/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("kensvin/image_classification") model = AutoModelForImageClassification.from_pretrained("kensvin/image_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 51f29aabba9faec9cdf0e930acd30affa34077921d805962e0aaa021b4a8bc3e
- Size of remote file:
- 344 MB
- SHA256:
- 1c2d04794ef421137a50f5960ad8e4c7a023e0482d6154fded77661d08fc4366
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