Capture your gear for free with TONEZONE3000

[DagMat]

try it and share a link to the tone from tonezone3000 here so we can listen to it!

As soon as I have time I will try it and share the results!

 

[Bumble]

As far as the wet/dry training goes, is there an ideal length of time to record &/or what to play to get the most accurate results? I’ve been trying to get around a minute of chords and single notes all over the neck and getting pretty good results, but keep wondering if there was something I could play that would optimize the training.

 

[2dor]

As far as the wet/dry training goes, is there an ideal length of time to record &/or what to play to get the most accurate results? I’ve been trying to get around a minute of chords and single notes all over the neck and getting pretty good results, but keep wondering if there was something I could play that would optimize the training.

The more diversified the data is, the better.
Steve's original training signal is about 3 minutes long but has a ton of diversity &, very important, dynamic range (low volume playing, hard hitting etc)

 

[staas]

As far as the wet/dry training goes, is there an ideal length of time to record &/or what to play to get the most accurate results? I’ve been trying to get around a minute of chords and single notes all over the neck and getting pretty good results, but keep wondering if there was something I could play that would optimize the training.

Totally agree with @2dor 's recommendation/ Steve Atkinson, the inventor of Neural Amp Modeler, has a good tutorial on his blog: https://www.neuralampmodeler.com/post/tonezone3000-training-made-simple

 

[JerEvil]

Totally agree with @2dor 's recommendation/ Steve Atkinson, the inventor of Neural Amp Modeler, has a good tutorial on his blog: https://www.neuralampmodeler.com/post/tonezone3000-training-made-simple

So what if I only want to make DI NAM captures?

 

[2dor]

So what if I only want to make DI NAM captures?

You can run the amp into a loadbox and get that signal as the WET. Or put a DI in between the amp & cab (something like the Behringer ULTRA-G GI100) and tap the DI signal off its XLR output.

 

[Shredder777]

I built something! It's called TONEZONE3000 (https://tonezone3000.com) and it's built on top of Nueral Amp Modeler (NAM) the open source project by Steve Atkinson. With this tool you can capture a digital model of your amps, pedals and signal chains for free.

Training/capturing tones is hard - modeling pedals are expensive, colab is frustrating/expensive, local set ups are daunting. My goal is to change that by making training simple, free and accessible. With TONEZONE3000, you can easily train models online, fast and free, with a slick UX.

Here are a few reasons why I've enjoyed TONEZONE3000 coming from colab / my local setup:

• Super fast and totally free training on RTX 4090s (no longer consuming my own resources)
• Dead simple workflow
• Cloud-based, so you can start training and close your computer
• Train multiple models concurrently
• An organized library of your tones
• Easily share your models with friends
• Preview your models with a range of DIs

Btw, you can train models with just a Dry/Wet Pair (DI and its matching stem). This has enabled me to create tones models from sessions I recorded years ago!

I’m sharing the beta to you now, and I'd love for you to train a model (or ten!) and share your feedback and models

Here's a capture of a Klon clone I built with my buddy: https://www.tonezone3000.com/tonezone3000/tones/klon-centaur-silver-clone-130

Amazing! Who is paying the hosting costs for the use of the 4090s? That is some serious time/electricity on the server side.

 

[eggpl@nt]

Amazing! Who is paying the hosting costs for the use of the 4090s? That is some serious time/electricity on the server side.

Pg3

Soooo I posted this and closed my computer, and was shocked by all the comments! Thank you so much for the kind words and feedback. Here are the answers to hopefully most of the questions:

Background: TONEZONE3000 was co-founded by me and my childhood friend Woody. We played in a band together and studied engineering at Georgia Tech. Our goal is to make capturing tones easy, accessible, and free :)

Funding: We are a part of a VC backed studio which allows access to some GPU resources. If TONEZONE3000 becomes a thing, we'll need to create a business plan (maybe a pro-tier?). Would love to hear what features you’d consider paying for! For now, everything is totally free!

GPUs: Your tones/models are trained in the cloud on RTX 4090s. We partnered with a handful of GPU providers for this.

File Storage: Your files are securely stored on Amazon S3, accessible only to you and those you share the link with. They are not visible to other TONEZONE3000 users, and we do not use them for any other purposes.

Privacy Policy / Terms: We launched TONEZONE3000 four weeks ago, without knowing if anyone would use it, so we didn’t prioritize a privacy policy or even an “About” page lmao. Now we’re working on a privacy policy and terms. Here’s the current draft but please let us know your feedback !!!

1. You own your models and audio files. TONEZONE3000 does not own them and does not have the right to sell them.
2. TONEZONE3000 may use the data for research and to improve our services.

One example of this is our new feature called "Best Fit." With "Best Fit," you get the same ESR faster without sacrificing quality. You can read more about it here: https://tonezone3000.com/best-fit

 

[staas]

Launched a bunch of updates to TONEZONE3000 today. Thanks to everyone who gave us feedback/ideas :)

• Share to ToneHunt: With a single click, TONEZONE3000 can now automatically upload your tone to ToneHunt. If you're unfamiliar, ToneHunt is a community for sharing and discovering tones. More exciting news next week
• Edit Tone: Easily update the gear type, name, and description.
• Improved Tone Details: Tone pages now display training type (Sweep or Dry/Wet) and the model's size/architecture.
• About Page: The usual plus some FAQs to help new users get started with capturing their tones!
• Privacy & Terms: Bottom line: you own the files you upload and the models you create. TONEZONE3000 will not sell them!

These features are live now! Check them out: https://tonezone3000.com

What should we build next?

 

[MirrorProfiles]

What should we build next?

You’ve done a great job at tackling some of the main barriers of entry for people and making it as simple as I can possibly imagine, so with that in mind:

- batch processing (both of training files, and for dealing with naming/metadata of them). Check out tools like Myriad and A Better Finder Rename for the kind of batch ideas I have in mind.
- more tools for organisation of files. Maybe using metadata to organise them into folders based on amp/channel/modes/date. Something that can update on the fly, like a smart itunes but for NAM files
- An easy process for making “hyper accuracy” models
- maybe something geared towards parametric models (maybe pedals are a good place to start?)
- ability to audition models with your own IR loaded (maybe this is possible already?)

I guess it’s looking at what is most tedious to do (naming/organising/training files), and then making a way to find what you need with the least fuss.

 

[staas]

You’ve done a great job at tackling some of the main barriers of entry for people and making it as simple as I can possibly imagine, so with that in mind:

- batch processing (both of training files, and for dealing with naming/metadata of them). Check out tools like Myriad and A Better Finder Rename for the kind of batch ideas I have in mind.
- more tools for organisation of files. Maybe using metadata to organise them into folders based on amp/channel/modes/date. Something that can update on the fly, like a smart itunes but for NAM files
- An easy process for making “hyper accuracy” models
- maybe something geared towards parametric models (maybe pedals are a good place to start?)
- ability to audition models with your own IR loaded (maybe this is possible already?)

I guess it’s looking at what is most tedious to do (naming/organising/training files), and then making a way to find what you need with the least fuss.

wow super helpful thank you!!!

 

[Mongillo19]

wow super helpful thank you!!!

Less helpful than Mirror but as someone who is absolutely new to even reamping. A video walkthrough of the whole process of using Tonezone would be cool!

I'm sure it's time consuming and may not be worth the squeeze but just a thought!

 

[staas]

Less helpful than Mirror but as someone who is absolutely new to even reamping. A video walkthrough of the whole process of using Tonezone would be cool!

I'm sure it's time consuming and may not be worth the squeeze but just a thought!

yea that's a really good idea! until then, this post from Steve Atkinson, the inventor of NAM, has a helpful guide how to use TONEZONE3000: https://www.neuralampmodeler.com/post/tonezone3000-training-made-simple

 

[2dor]

What should we build next?

It would be awesome to have a checkbox, instead of a drop-down menu, to select all the architectures we want from 1 single reamp.

To explain myself: I have a reamp for which I want to train models with all architectures (Standard, Lite, Feather, Nano).

Right now, I need to upload the same reamp for each architecture.

Even if TZ3000 in the backend seizes different GPUs for the training & runs separate instances, having a checkbox that lets me specify which architectures I want would be slightly better from a user experience PoV.

 

[staas]

It would be awesome to have a checkbox, instead of a drop-down menu, to select all the architectures we want from 1 single reamp.

To explain myself: I have a reamp for which I want to train models with all architectures (Standard, Lite, Feather, Nano).

Right now, I need to upload the same reamp for each architecture.

Even if TZ3000 in the backend seizes different GPUs for the training & runs separate instances, having a checkbox that lets me specify which architectures I want would be slightly better from a user experience PoV.

Got it! We will prioritize this feature for our roadmap.