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In Algorithm part , you have used the pkl file for building the model (For eg mcunet-5fps.pkl in assets/mcu_models).
Could you please let me know how you have create the model and how you have convert the model into pickle quantized (int 8 bit) format.
Thanks,
Chinmay
The text was updated successfully, but these errors were encountered:
I would like to know too. I was looking the structure of mbv2-w0.35.pkl and what I found was that it is a dictionary, that contains the following keys: first_conv, blocks, feature_mix and classifier.
first_conv seems to be a dictionary with 10 elements, probably containing information about the first convolutional layer of the model. blocks is a list with 17 elements, likely representing the intermediate blocks or layers of the neural network. feature_mix is set to None. And classifier is a dictionary with 6 elements, which likely correspond to the final classification layer of the model.
I didn't find any function library that saves the model like that, I tried to make my own function, but I got some problems. Did you discover how the authors have created the model and how they convert it into pickle quantized format?
Hi,
In Algorithm part , you have used the pkl file for building the model (For eg mcunet-5fps.pkl in assets/mcu_models).
Could you please let me know how you have create the model and how you have convert the model into pickle quantized (int 8 bit) format.
Thanks,
Chinmay
The text was updated successfully, but these errors were encountered: