Image Classification
Transformers
TensorBoard
Safetensors
PyTorch
vit
huggingpics
Eval Results (legacy)
Instructions to use jinnn8/Pizza with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jinnn8/Pizza with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jinnn8/Pizza") 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("jinnn8/Pizza") model = AutoModelForImageClassification.from_pretrained("jinnn8/Pizza") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 68d4be67bbee8c0441117d8a11044881a5fc00b82b86571a60f3a868709bd214
- Size of remote file:
- 59.2 kB
- SHA256:
- 7dacc67a3a81ab17625c5bc654f02d8c1fa98c721ff13d53a0360375b5c7584b
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