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:
- 4b7659161bf46334de14dadab629c019006f15bd665e8c50298dac9d18b960fa
- Size of remote file:
- 110 MB
- SHA256:
- 611bf6c977a11e8ecd3ca5f56d694dca8769e5bbd6510d3280968528eb4f47c2
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