schema_version: 1.0.0
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