Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use johnnydevriese/vit-airplanes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use johnnydevriese/vit-airplanes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="johnnydevriese/vit-airplanes") 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("johnnydevriese/vit-airplanes") model = AutoModelForImageClassification.from_pretrained("johnnydevriese/vit-airplanes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fed7431331a407acf1bb8b7e2dce062a4386dc566fe0bacc787fc8b1f09425a4
- Size of remote file:
- 3.06 kB
- SHA256:
- 7834cd57d542ddc4329f4748d5c4bb84bdeb58192ddcd479467afe9aa73522bf
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