Instructions to use tzhao3/vit-MNIST with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tzhao3/vit-MNIST with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="tzhao3/vit-MNIST") 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-MNIST") model = AutoModelForImageClassification.from_pretrained("tzhao3/vit-MNIST", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from tzhao3/vit-MNIST: direct link, hf CLI and curl.
- Browser
- Download file 3.84 kB
-
https://huggingface.co/tzhao3/vit-MNIST/resolve/main/training_args.bin
- Command line
-
hf download hf://tzhao3/vit-MNIST/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/tzhao3/vit-MNIST/resolve/main/training_args.bin
3.84 kB
- Xet hash:
- 8f39b4af3df6fc217459ba8ee8341f3baaed83c813c0f1147a88f80ba0309a1a
- Size of remote file:
- 3.84 kB
- SHA256:
- a9f5eb0678bc3c656f95df644dfdde83bfc35974f3071ba19551a60888e56506
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