Instructions to use peter881122/freeway_vit_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peter881122/freeway_vit_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="peter881122/freeway_vit_Model") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("peter881122/freeway_vit_Model") model = AutoModelForImageClassification.from_pretrained("peter881122/freeway_vit_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7da6da7e5b12639606cc09cfa75afb2598d8bc325cd64b2ea8544b4d7bdd9c42
- Size of remote file:
- 5.11 kB
- SHA256:
- 0d52dc61ce4d59d3261f013347133509301fe2fa74c59396bdcefe41be3a7107
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