Instructions to use kawchar85/image-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kawchar85/image-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="kawchar85/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("kawchar85/image-classification") model = AutoModelForImageClassification.from_pretrained("kawchar85/image-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec656c8c1cbfb494188a84aaddaee9e220aebb72a5824204a69672d434914d54
- Size of remote file:
- 5.24 kB
- SHA256:
- 3ce4ea3ec6807755de1fd1701aef519291b0b1dcb658b1cc8b6586eae1406fd2
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