Instructions to use prithivMLmods/Recycling-Net-11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Recycling-Net-11 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Recycling-Net-11") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/Recycling-Net-11") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Recycling-Net-11", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-392/optimizer.pt from prithivMLmods/Recycling-Net-11: direct link, hf CLI and curl.
- Browser
- Download file 687 MB
-
https://huggingface.co/prithivMLmods/Recycling-Net-11/resolve/main/checkpoint-392/optimizer.pt
- Command line
-
hf download hf://prithivMLmods/Recycling-Net-11/checkpoint-392/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/prithivMLmods/Recycling-Net-11/resolve/main/checkpoint-392/optimizer.pt
687 MB
- Xet hash:
- ff066d0a3eef8516901b4d4fa45e6cdf7e62252dd9197f5338c54839e6765115
- Size of remote file:
- 687 MB
- SHA256:
- f36c03232783a4af944afea24a8f7aab78d509f419b98d6d4ec26c2547f385d6
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