Instructions to use prithivMLmods/Augmented-Waste-Classifier-SigLIP2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Augmented-Waste-Classifier-SigLIP2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Augmented-Waste-Classifier-SigLIP2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/Augmented-Waste-Classifier-SigLIP2") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Augmented-Waste-Classifier-SigLIP2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c1f3436e2e0f222c0a9fe4d499b3698bf3be03a9b7d71bec34b39256f9e459c
- Size of remote file:
- 5.3 kB
- SHA256:
- de42aa43c631955f61143c2f68f1a4b33fbe517784032f7832f74bb08c64a27d
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