Instructions to use optimum/vit-base-patch16-224-neuronx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use optimum/vit-base-patch16-224-neuronx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="optimum/vit-base-patch16-224-neuronx") 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("optimum/vit-base-patch16-224-neuronx") model = AutoModelForImageClassification.from_pretrained("optimum/vit-base-patch16-224-neuronx") - Notebooks
- Google Colab
- Kaggle
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license: apache-2.0
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license: apache-2.0
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Exported with
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```bash
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optimum-cli export neuron --model facebook/deit-base-patch16-224 --batch_size 1 --task image-classification vit_neuron/
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```
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