Steven Atkinson

Got the nits and did a bit of cleanup on the documentation in [Eraz1997/main](https://github.com/sdatkinson/neural-amp-modeler/tree/Eraz1997/main). Closing this PR and we'll merge there 👍🏻

@DimGakis that sounds pretty hacky. Was the file you used _based on_ v1_1_1.wav? Or how is it related to one of the standard reamp files? (Assuming it is). If it's...

But the fact that it doesn't "soft match" any of the standardized files means that something is different in it that makes it not have something that it needed to...

Directions for using the CLI trainer: https://github.com/sdatkinson/neural-amp-modeler/tree/main#the-command-line-trainer-all-features

> Directions for using the CLI trainer: https://github.com/sdatkinson/neural-amp-modeler/tree/main#the-command-line-trainer-all-features Updated now that there's a ReadTheDocs (hooray!): https://neural-amp-modeler.readthedocs.io/en/latest/tutorials/command-line.html I'm thinking to add a tutorial for how to use NAM if you have...

Thanks for your very thorough Issue, @KaisKermani 🙂 I see two different topics in here: 1. Using ESR and DC terms in the loss function, and 2. making an architecture...

@mikeoliphant > Any tips on how to best go about allowing a larger receptive field for LSTM models (right now it is hardcoded to 1)? There is an "input_size" property,...

@38github > > For NAM, you could do this in a pinch by using `._esr_loss()` instead of `._mse_loss()` > > I tried this with LSTM just to see what would...

> there's a myriad of different pieces of equipment out there with such a diverse set of controls, so I am not sure how viable something like this would be...

Now it's in the advanced settings (GUI) and visible in Colab. I guess this is just a tutorial on how to look at the waveforms?