Instructions to use INC4AI/vit-base-patch16-224-int8-static-inc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use INC4AI/vit-base-patch16-224-int8-static-inc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="INC4AI/vit-base-patch16-224-int8-static-inc") 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("INC4AI/vit-base-patch16-224-int8-static-inc") model = AutoModelForImageClassification.from_pretrained("INC4AI/vit-base-patch16-224-int8-static-inc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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# INT8
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### Post-training static quantization
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- accuracy
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# The INT8 model based on vit-base-patch16-224 which finetuned on imagenet-1k
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### Post-training static quantization
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