Instructions to use DamarJati/GreenLabel-Waste-Types with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DamarJati/GreenLabel-Waste-Types with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="DamarJati/GreenLabel-Waste-Types") 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("DamarJati/GreenLabel-Waste-Types") model = AutoModelForImageClassification.from_pretrained("DamarJati/GreenLabel-Waste-Types", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from DamarJati/GreenLabel-Waste-Types: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/DamarJati/GreenLabel-Waste-Types/resolve/main/training_args.bin
- Command line
-
hf download hf://DamarJati/GreenLabel-Waste-Types/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/DamarJati/GreenLabel-Waste-Types/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- c1b6c446e9b7ba2fe04c2eac9a70f74129a4413ebb0e572e107c768960dff91b
- Size of remote file:
- 4.09 kB
- SHA256:
- f9decd37c98f64c57de47e44e7441d9e7c01627270950601927336d5480cd2b5
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