Instructions to use ethanwan/Trash-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ethanwan/Trash-Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ethanwan/Trash-Classifier") 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("ethanwan/Trash-Classifier") model = AutoModelForImageClassification.from_pretrained("ethanwan/Trash-Classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 30ace656d4f0c8afbbc9356ccde8ef9901a5a7eca2058ece49dff2f51f79ee8f
- Size of remote file:
- 343 MB
- SHA256:
- 41495de0069cd1c24474368cb56a988292c1ef8620eb509b136916004a3e427b
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