Hey all - late to the thread here, but I wanted to share my solution for saving-loading models.
I train in the notebook, save the model, and then load the model when backtesting. I haven't gotten far enough to need automated training in the backtest code.
Here's a thread where I detail how to save/load using PyTorch:
https://www.quantconnect.com/forum/discussion/9245/how-to-save-a-status-object-in-objectstore/p1
And here is a thread where I ask Jared Broad about GPU training on QC (still not fully answered):
https://www.quantconnect.com/forum/discussion/72/math-libraries/p1
Overall, I'm torn - I want to use QC because of the data and backtesting capabilities, but I'm unable to train any heavy models due to 1. the lack of GPUs and 2. lack of visibility into my resource consumption - sometimes my models freeze during training and I suspect it's got something to do with memory consumption, but I can't tell for sure.
Best,