# Inception model optimization on Qualcomm NPU
[inception_snpe_qualcomm_npu](https://github.com/microsoft/Olive/tree/main/examples/snpe/inception_snpe_qualcomm_npu)

# Cifar10 optimization with OpenVINO for Intel HW
[cifar10_openvino_intel_hw](https://github.com/microsoft/Olive/tree/main/examples/cifar10_openvino_intel_hw)

# BERT optimization with QAT Customized Training Loop on CPU
[bert_qat_customized_train_loop_cpu](https://github.com/microsoft/Olive/tree/main/examples/quantization_aware_training/bert_qat_customized_train_loop_cpu)

# ResNet optimization with QAT Default Training Loop on CPU
[resnet_qat_default_train_loop_cpu](https://github.com/microsoft/Olive/tree/main/examples/quantization_aware_training/resnet_qat_default_train_loop_cpu)

# ResNet optimization with QAT PyTorch Lightning Module on CPU
[resnet_qat_lightning_module_cpu](https://github.com/microsoft/Olive/tree/main/examples/quantization_aware_training/resnet_qat_lightning_module_cpu)

# SqueezeNet latency optimization with DirectML
[directml/squeezenet](https://github.com/microsoft/Olive/tree/main/examples/directml/squeezenet)

# Stable Diffusion optimization with DirectML
[directml/stable_diffusion](https://github.com/microsoft/Olive/tree/main/examples/directml/stable_diffusion)

# BERT optimization with Intel® Neural Compressor Post Training quantization on CPU
[bert_inc_ptq_cpu](https://github.com/microsoft/Olive/tree/main/examples/bert_inc_ptq_cpu)

# Whisper optimization using ORT toolchain
[whisper](https://github.com/microsoft/Olive/tree/main/examples/whisper)