Image Classification
Transformers
Safetensors
English
siglip
Trash
Classification
Net
biology
SigLIP2
Instructions to use prithivMLmods/Trash-Net with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Trash-Net with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Trash-Net") 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/Trash-Net") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Trash-Net") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd3bfdbf2c1da50738f7de3420332055818018ed9a3d0cbfc0ede339874067b7
- Size of remote file:
- 687 MB
- SHA256:
- 68b7bb1207871f6c09a3c5219fe32e00b36831c7d67c0331f7e9b2d86857b81b
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