Instructions to use tzhao3/vit-GTSRB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tzhao3/vit-GTSRB with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="tzhao3/vit-GTSRB") 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("tzhao3/vit-GTSRB") model = AutoModelForImageClassification.from_pretrained("tzhao3/vit-GTSRB", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from tzhao3/vit-GTSRB: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/tzhao3/vit-GTSRB/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://tzhao3/vit-GTSRB/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tzhao3/vit-GTSRB/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- a055a41f2921d119016f4821aa91942e49efb7a78eee18a3bb9b2bd6a9356d35
- Size of remote file:
- 343 MB
- SHA256:
- 605982f335d91fc4ddaad51caf709e6385403f28c2e8f928e08ef2ce8a62703d
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