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post-training-quantization

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QuantLab-8bit is a reproducible benchmark of 8-bit quantization on compact vision backbones. It includes FP32 baselines, PTQ (dynamic & static), QAT, ONNX exports, parity checks, ORT CPU latency, and visual diagnostics.

  • Updated Sep 25, 2025
  • Python

In this repo you will understand .The process of reducing the precision of a model’s parameters and/or activations (e.g., from 32-bit floating point to 8-bit integers) to make neural networks smaller, faster, and more energy-efficient with minimal accuracy loss.

  • Updated Aug 11, 2025

Hardware-verified SNN-equivalent intrusion detection system (IDS) on STM32N6 Neural-ART NPU. INT8 quantized MLP achieving 0.4561ms inference at 800MHz. First publicly documented IDS on a commodity MCU NPU with T=1 SNN-ANN equivalence validation.

  • Updated Mar 9, 2026
  • Python

EfficientNetV2 (Efficientnetv2-b2) and quantization int8 and fp32 (QAT and PTQ) on CK+ dataset . fine-tuning, augmentation, solving imbalanced dataset, etc.

  • Updated May 4, 2024
  • Jupyter Notebook

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