Web Reference: Static quantization method first runs the model using a set of inputs called calibration data. During these runs, we compute the quantization parameters for each activations. Static quantization involves quantizing both the model weights and activations before performing inference. Since the range of activations can vary depending on the input data, static quantization requires a calibration step. The ORTQuantizer class can be used to quantize statically your ONNX model. Below you will find an easy end-to-end example on how to quantize statically distilbert-base-uncased-finetuned-sst-2-english.
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