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For research proposes, you can run it with cpu backend by just modifying the config yaml.
I am not similar with deployment in production environment. Maybe you can use the saved checkpoints to re-construct your model (or export it in ONNX)?
When we have trained the quantization model, how to deploy it in cpu backend?
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