File size: 1,117 Bytes
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report_type: vision-classification
task_type: image-classification
title: DeiT-Tiny INT8
description: >-
INT8-quantized compact vision transformer for 1000-class image classification, designed for
efficient inference on ARM edge devices with ExecuTorch and XNNPACK. It uses static symmetric
per-channel quantization and ImageNet-style preprocessing, producing raw logits for top-k
classification while reducing model size, latency, and memory use with minimal accuracy impact
compared with the FP32 baseline.
id: Arm/deit-tiny-int8-xnnpack-executorch
filename: deit_raspberry_executorch_optimized.pte
base_model_id: facebook/deit-tiny-patch16-224
vendor: Meta
base_model_url: https://huggingface.co/facebook/deit-tiny-patch16-224
weight_dtype: int8
profile: Arm-Optimized
optimization:
optimized_by: Arm
quantization:
method: PTQ-static
weight_bits: 8
activation_bits: 8
symmetric: true
mode: static
weight_granularity: per-channel
calibration:
dataset_name: ImageNet-1k
sample_count: 1000
selection: random
model_size_mb: 6.62
parameter_count: 5717416
format: pte
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