Tang Kaihui

Hi @yingmuying Thanks for raising this issue. You can use dynamic quantization for the model: ``` from neural_compressor.config import PostTrainingQuantConfig from neural_compressor import quantization config = PostTrainingQuantConfig(device='cpu', approach='dynamic', domain='auto') q_model...

Hi @yingmuying , Thanks for your reply. The `PostTrainingQuantConfig` is used to configure quantization parameters, you can refer to [config-docstring](https://github.com/intel/neural-compressor/blob/e22c61ede2942f7f1ba1cf9e480491371184bb32/neural_compressor/config.py#L1195C1-L1291C8) to understand the meaning of parameters. There are some other...

> Can we 1) create an `InputCaptureModule` during the prepare stage and 2) initialize an original `AutoRound` at the convert stage, receiving a) the original model and b) the data...