Instructions to use bryandts/garbage_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bryandts/garbage_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="bryandts/garbage_classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("bryandts/garbage_classification") model = AutoModelForImageClassification.from_pretrained("bryandts/garbage_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from bryandts/garbage_classification: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/bryandts/garbage_classification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://bryandts/garbage_classification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/bryandts/garbage_classification/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- 8147737a5a00e8c92e5019236f2f8094834dc3f81d233720f23e95d0cc02ec6c
- Size of remote file:
- 343 MB
- SHA256:
- ee244ed1b16644c4b54c2399b1461b823e3e7367aea273f6310c05f7a5f3568a
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