Instructions to use autoevaluate/image-multi-class-classification-not-evaluated with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use autoevaluate/image-multi-class-classification-not-evaluated with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="autoevaluate/image-multi-class-classification-not-evaluated") 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("autoevaluate/image-multi-class-classification-not-evaluated") model = AutoModelForImageClassification.from_pretrained("autoevaluate/image-multi-class-classification-not-evaluated") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa1edcda032a69a561c7b1fa6b9dbb04f3af8a9083d37e70aeb48d65d3898e71
- Size of remote file:
- 3.31 kB
- SHA256:
- 25b3008f2df2db06844e1c7300c08af1eec38c6580f96246ac4dc0758c823eb2
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