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:
- 610d7aff4cfd598ae3a7b0908e4fd2f0037836623eee35446ca6b9ee7812e598
- Size of remote file:
- 26.6 kB
- SHA256:
- 40061033059a59c924576bdcb15e6b817ec45ea3d871ae40c17c149fe1d9ddff
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