Instructions to use as-cle-bert/bus-deit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use as-cle-bert/bus-deit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="as-cle-bert/bus-deit") 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("as-cle-bert/bus-deit") model = AutoModelForImageClassification.from_pretrained("as-cle-bert/bus-deit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from as-cle-bert/bus-deit: direct link, hf CLI and curl.
- Browser
- Download file 4.86 kB
-
https://huggingface.co/as-cle-bert/bus-deit/resolve/main/training_args.bin
- Command line
-
hf download hf://as-cle-bert/bus-deit/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/as-cle-bert/bus-deit/resolve/main/training_args.bin
4.86 kB
- Xet hash:
- eec7270b24d47a05e8aca6a3969b5c69c7571f1fe34c8a1c35ffc41ccdb87035
- Size of remote file:
- 4.86 kB
- SHA256:
- a0251e08256acb395a5ecdc91af3a1b616b8fafba563515961623420a1e3b703
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