Instructions to use DataScienceProject/Vit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DataScienceProject/Vit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="DataScienceProject/Vit") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DataScienceProject/Vit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from DataScienceProject/Vit: direct link, hf CLI and curl.
- Browser
- Download file 28 Bytes
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https://huggingface.co/DataScienceProject/Vit/resolve/0012df3d2d88ddac7899e2fa68e926a824b2f29a/README.md
- Command line
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hf download hf://DataScienceProject/Vit@0012df3d2d88ddac7899e2fa68e926a824b2f29a/README.md
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curl -L -o README.md https://huggingface.co/DataScienceProject/Vit/resolve/0012df3d2d88ddac7899e2fa68e926a824b2f29a/README.md
28 Bytes
metadata
license: unknown