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:
- 657543df064cca2fb22a20d7fe5e7cadb073aa62f464d8e4963042fab10ba4a4
- Size of remote file:
- 343 MB
- SHA256:
- a42bf0283b69785b7dde37f3a724271e91add0b0c5ecc535cbfd7fbea546124d
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