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-98/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-98/optimizer.pt
- Command line
-
hf download hf://prithivMLmods/Recycling-Net-11/checkpoint-98/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/prithivMLmods/Recycling-Net-11/resolve/main/checkpoint-98/optimizer.pt
687 MB
- Xet hash:
- 022febea5002d16b9076269eab52cab0f799280d32de0315c8665a0cf460e1d3
- Size of remote file:
- 687 MB
- SHA256:
- 3b8d249e216fadfd52d9b29e1ddf3ed832940e9eec2709ca17120114d80f38d0
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