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:
- d267539d966e2496f3c4a3fecdb35e348dcea942540c35f15e101f95de168551
- Size of remote file:
- 343 MB
- SHA256:
- 09a802e862fce3695a2764b29d32e623951b89279086ea76a97fd415f1a8cf39
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