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 training_args.bin from bryandts/garbage_classification: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/bryandts/garbage_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://bryandts/garbage_classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/bryandts/garbage_classification/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 5033cd114ef08cf7aced1e6481fbe6be32bd9f2309f11aad1aa9b83fd6d48ba8
- Size of remote file:
- 4.09 kB
- SHA256:
- 8631acbb3ef2a14a20ea1f45fa016b52d3717276f4cc975b136173dd67c72a02
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