What I am trying to achieve here is to emulate an analog guitar pedal through the use of machine learning.
Here is what I did so far

Recorded myself playing guitar and split the channel (1 clean, 1 through the analog reverb pedal)
As a result I ended up with 2 wav files
I compiled the 1st repo on google collab and uploaded both files (clean/input file, target/output file)
** When the code finished running, I got a .pt file
** torch.save(model, "./reverb_full.pt") files.download("./reverb_full.pt")

Moving on to repo #2. I compiled this repo on my own computer with anaconda.
** This repo basically takes a json file (model/network weights) and creates a VST3 plugin to later on use it on a DAW software (pro tools for example, or any other software to record music)

I asked the owner of the second repo how to convert .pt files to an acceptable json formatted file and this is what he said How do I transform .pt files to json ? · Issue #46 · jatinchowdhury18/RTNeural · GitHub 1
Since I am fairly new with all this, maybe the response makes more sense to you.
Thank you so much for taking the time to even look into this!!
This is an example of the json file the second repo expects RTNeural-example/neural_net_weights.json at main · jatinchowdhury18/RTNeural-example · GitHub