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:
- 080bebaf74f1c95c1493866c83f325f7dae01f17c0c319bcfdc9d9f22dc5a914
- Size of remote file:
- 687 MB
- SHA256:
- 6b1cb6d6354f0e37cfcb4ff57e7b727b6511b78451a09495f26da4a7579781cd
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