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Hi, dear author:
The memory reduce is very attractive and will benefits its application. I wonder does current onnx support the techniques you proposed and inference with onnxruntime framework?
The text was updated successfully, but these errors were encountered:
Thank you for your interest in our work! We haven't tried ONNXRuntime yet, we think it is applicable. MixDQ adopts the standard and deployment-friendly quantization scheme, We have already tested MixDQ with the pytorch_quantization deployment tool.
Hi, dear author:
The memory reduce is very attractive and will benefits its application. I wonder does current onnx support the techniques you proposed and inference with onnxruntime framework?
The text was updated successfully, but these errors were encountered: