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 training_args.bin from tzhao3/vit-GTSRB: direct link, hf CLI and curl.
- Browser
- Download file 3.9 kB
-
https://huggingface.co/tzhao3/vit-GTSRB/resolve/main/training_args.bin
- Command line
-
hf download hf://tzhao3/vit-GTSRB/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/tzhao3/vit-GTSRB/resolve/main/training_args.bin
3.9 kB
- Xet hash:
- c8680fe437e6e02247ab9b9357f2af433ed9791854744f41295598d9d5a9af21
- Size of remote file:
- 3.9 kB
- SHA256:
- af2a0ce70eeb22dbb827f8633cbf625ef72b92aadd1a57c78ef3ee946ec7876b
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