r/NAM_NeuralAmpModeler

NAM users that record songs with multiple guitar tracks and parts, what’s your CPU management workflow?

This is something I’m trying to understand as I set up a NAM workflow for a co-writer, who uses an M5 with 24GB RAM.

I use Quad Cortex and my recording gets laid down already baked, so this is the one thing I haven’t had to think about until now. What’s your workflow when it comes to managing CPU performance during recording where you’d have multiple tracks with a NAM running (quad tracking a part), are you bouncing in place as you go?

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u/overcloseness — 21 hours ago

How to configure calibrated captures?

I’ve recently started playing around with NAM captures and I’m having a hard time understanding how to use the calibrated amps. Some articles that I’ve read have instructed to set my audio interface gain (using a Scarlett Solo) at 0 and enter the maximum input level in the NAM plugin as 12dBu. Other articles have instructed to not set my gain at 0, and instead turn it up until just below clipping and then adjust the NAM level accordingly (e.g., decreasing the level as gain increases I guess?). I’m not sure which advice to go off of.

Here’s what I’ve found through experimentation—when I use a calibrated amp head (with IR), set my interface gain to 0, enter 12dBu in the NAM plugin settings, the tone I get sounds clipped and very “digital” if that makes sense. When I turn my interface gain up to just under clipping (right at 9 o’clock) and decrease the maximum input level to somewhere around 4dBu, the sound is much cleaner. However, I do have to turn the output significantly to get a good volume.

I guess my question is—am I doing this right? I haven’t been able to find a super clear guide online, so I’m kinda just going by ear, but I’m also not sure how much to trust my ear since I’m very new to the world of amp sims (and amps in general—I’ve only been playing electric for about 6 months after years of playing exclusively acoustic). I think the stock GarageBand amp sims sound better than most of my attempts at configuring NAM, so that tells me I’m probably doing something wrong considering all of the praise I see for many top rated captures online.

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u/thatguysbestfriend — 1 day ago
▲ 22 r/NAM_NeuralAmpModeler+1 crossposts

Blackstar Beam Mini

It just arrived! I'm really looking forward to trying out this integrated Tone3000 software for NAM files. Who else already has one and has feedback or suggestions?

u/SnowCapBoofing — 3 days ago

A partial solution for people with a lot of noise coming through NAM

In the past, I've had luck removing noise from recordings, using rendered post processing. Decided to look up to see if there's a real time denoiser vst, and came across the Bertom Denoiser. It's pay what you want, even $0. I threw it on my guitar effects chain, right after Neural Amp Modeler, and it greatly reduced the noise from my amp model, without sacrificing guitar audio quality. It's not 100% gone, but I'd say it's about 85% gone. Much better sound. Just thought I'd share because I've seen some discussion about noise in the past. Lemme know if it works for you guys, or if you have a better solution.

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u/fkenned1 — 2 days ago

Looking for THRASH/DEATH metal

looking for some good thrash/death metal full rigs. I’m really new to using this program (enjoy it so far) and have been using it to demo a new record. found a few ones I like… I feel like I’m “getting there”

having said that I don’t know if I’m satisfied. I want the best I can get for this. I have an esp ev1000 with active pick ups. Could someone help me with some ideal settings? should I be dialing back in “input“ on the nam app? should I be dialing back on my interface? I usually try to “keep it in the top yellow” on my volt interface. I use logic fyi. any help would be appreciated. Been playing in bands for years and I finally feel like I am able to demo at home digitally.

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u/Trvekingofstjames — 2 days ago
▲ 20 r/NAM_NeuralAmpModeler+1 crossposts

We added NAM support to Stratus. Preview is live, would love feedback!

Hey everyone! 👋 We just shipped NAM A2 support on Stratus as a preview, with full launch coming in the next week or so. Running natively, no conversion. Would love your feedback!

If you have a Stratus: Update the app (if you're on Android) or join the TestFlight (if you're on iOS) and try it out! NAM A2 profiles load directly from TONE3000.
https://testflight.apple.com/join/bcRfDFjz

Don't have a Stratus? You can still download the Chaos Audio app and explore the TONE3000/NAM browser interface. We'd love feedback on the experience even without hardware!

We've been exploring NAM on Stratus for years, so I want to give a major shoutout to Steve Ack and TONE3000 for finally making it possible with A2. ❤️

Link: https://chaosaudio.com/pages/neural-amp-modeler

u/landonmccoy — 4 days ago
▲ 111 r/NAM_NeuralAmpModeler+2 crossposts

VoLum 1.0 Released - Free NAM-based Guitar Plugin with PRE and POST Section, Dual Amp and much more

Hi Guys,

I posted a month ago with a WIP state about my Guitar Plugin.

It's now released and I'm really happy with it.

I have worked on a lot of features since last shared:

  • Mac Support
  • ASIO Standalone fix (to support multichannel audio interfaces)
  • POST Amp Section with 3 Delays and 5 Reverbs
  • PRE Amp Section with 2 NAM Pedal Blocks (hand selected high end guitar pedals profiled by me) and a Compressor inspired by UAD 1176
  • Dual Amp Support for Stereo Rigs
  • Added Metronome and Tuner
  • Added a Diezel Herbert late MK1
  • Clipping Safety

Here is how it's used and sounds: https://www.youtube.com/watch?v=-J-rSKlvL8A

You can download it here: https://github.com/guitarlum/VoLum/releases/tag/v1.0.0

User Guide: https://github.com/guitarlum/VoLum/blob/main/docs/user-guide.en.md

Follow me on Github: https://github.com/guitarlum/VoLum

Thank you already so much for the feedback given in the first thread!

I hope you enjoy it!

u/guitarlum — 5 days ago

Open source bass plugin built on NAM

Been loving NAM and using it heavily for about two years now! It's replaced almost all of my digital amps for guitar and bass, but I got tired of the workflow friction of splitting a bass signal, compressing the low end, and distorting the high end. Ended up building a free, open source plugin over top of NAM that emulates the workflow of some of the more modern bass processing plugins for heavy music with split band processing, built in compression, and distortion. All the distortion is handled via loading NAM captures. It's working great for me, so I put a little documentation on it and wanted to share it with the community in an attempt to give back. There's two plugins in the repo (the other is an IR loader with static and dynamic blending), and a folder with some of the IRs and NAM captures I made from my own gear that I use regularly.

https://github.com/gianni-cappelletti/October-Production-Co

u/great_northern_hotel — 11 days ago
▲ 5 r/NAM_NeuralAmpModeler+1 crossposts

HELP! im very new and very confused.

Hello, I use a Scarlet 2I4 hooked up to my laptop running NAM or Amplitube and I wanted to model an amp to practice with. When I model it in NAM its so delayed its impossible to practice with. Am I meant to practice with it? or is it only to be used for recording? I also wondered if I was able to run my guitar to my scarlet to nam then to my amp but when I do that I only get my dry guitar sound

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u/nashytr — 9 days ago

Does NAM calibration level depend on the playback dBFS level of the training file?

I've searched multiple Youtube videos and forum threads but am still confused.

Basically I have an interface with a max 14.5dBu output level, which I plan to capture some pedals with. No re-amp box, but my understanding (after doing thorough research) is that re-amping is not necessary at all and is simply a viral internet myth (anyway not the point of this post). So my current signal path looks like:

DAW TTSv10 training file -> interface out -> OD pedal -> interface in -> recording in DAW

I'm thinking to lower the training file volume to provide some headroom post-pedal. My question is, if I lower the output level of the training file by say, 4.5dBFS (the audio file peaks at roughly 0dBFS. so after attenuation the peaks are around -4.5dbFS in my DAW) does that make my correct calibration metadata 10dBu instead of 14.5dBu? That makes the most sense to me in my head, but please explain to me if I'm wrong. Thanks.

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u/Altruistic-Stuff2158 — 10 days ago

Neural Space: Play NAM profiles on iPhone/iPad

Been working on creating an app for iphone/ ipad that processes guitar tone. Broadly the app will-

Feature 1650 stock amp profiles
Support NAM profiles
The ‘Gravity’ feature lets you enhance your existing NAM profiles, reshapes the behaviour of capture for richer harmonics and tonal depth.
Stock amps are tonally spaced on a map. Similar sounding amps are grouped together. If you move further away from an amp on the map, gravity does it’s work. It’s a great place to discover tones.
Record your tones, record video from the app, play alongside backing tracks.
Tonematch EQ helps you reach your desired tone
iPad only features: Perform mode will let you control the app via midi - bluetooth/ cable will be supported. Recording section will be a DAW like setup where you can lay down, edit multiple tracks.

Hope to post some demo’s soon. The app is still being developed

u/Mysterious-Day-3200 — 13 days ago

Acoustic tone from electric guitar?

Hey, NAMmers!

TL;DR; if you own a guitar with combination of a magnetic and piezo pickup - we need you!

Yesterday I discovered NAM and I got very very excited! Today I already started capturing all my uncomplicated analog stuff and exploring tone3000.

For capturing and training I use hardcore Python and NVIDIA GPU, as I am also a fan of ML, PyTorch and Lightning (if you now what I mean).

Now the idea: Can we get a natural piezo acoustic tone from an electric guitar?

It would be cool if it would possible to get acoustic tone playing on singles/humbuckers. I know there modules in digital modellers but those are (I believe so) combination of dynamic compression and EQ.

I think we need to try to do it NAM way.

What is the plan?

We need to gently ask those of you who are lucky enough to have Godins, ESPs, PRSes, Music Mans or any other guitar with the combination of electric and piezo pickups. Also the guitar must have two separate outputs so you could record both of them at the same time in isolation.

So the setup must be:

- connect both outputs into two Hi-Z inputs of a sound card

- no processing on either output (we need natural original guitar tone both for electric and piezo pickups), if you are absolutely sure about your piezo tone - you can use a nice hardware compressor and/or an EQ for the piezo output. So all your unique hardware will be part of the final model. Absolutely no spatial effects (delay, reverb). Absolutely no any processing for the recording of the magnetic pickup.

- set piezo eq to some neutral flat settings and maximum possible level without clipping

- record two tracks: one for the electric pickup and one for the piezo pickup

Playing must be:

- record multiple individual notes with different level of volume

- record chords with different levels of volume

- record artificial harmonic with different levels of volumes

- record strumming with different levels of volume

- record different random picking noises with different levels of volume

- record all kind of insanely crazy string actions, slides, picking, kicking, licking

- if you have a tremolo bar would be nice to make a dive bomb

- play on different strings and in different positions

- switch the electric pickup switcher to another magnetic pickup and repeat

- would be nice to have 3-5 minutes or even more of different sounds, tones, and playing in different styles.

You do not have to play melodic and professional, basically it is totally OK if you cannot play at all, we just need sound sample pairs.

Result:

After all the result is a pair of WAV tracks. Would be nice if you can record them in 48kHz and 24bit, as this is default sample format for NAM. Pack both WAV tracks, compress into ZIP archive and share with the community.

The task overall is much harder and noisier than a normal NAM training, but the more examples we have, the more robust the training will be.

Success is not guaranteed, this is just an experiment, but I promise I will apply all my skills.

Also I believe here we have a lot of enthusiasts who also know about `input.wav`, `output.wav` and `nam-full` BASH script.

UPD1:

I found https://www.tone3000.com/tones/di-guitar-acoustic-simulator-50323 and it sounds pretty good with the removed low frequencies and a compressor on top.

UPD2:

As a proof of concept I created a NAM model using a good and expensive VST3 acoustic guitar plugin, so I could use it live with a NAM hardware player.

I cannot share the NAM model itself, as it will definitely be a violation of the license. But I can share the example.

https://drive.google.com/drive/folders/1cOmIiGZGOoj0bMIduDsrNoURJTeGtCkn

- `input.wav` - what I used as input for the training (the standard `input.wav` didn't work well). You will need to record something like this, the longer the better, the more diverse the better.

- `acoustic-test.mp3` - the example how the final NAM capturing model works, I've used a stratocaster with middle pickup.

u/mz876129 — 11 days ago

1.9ms round-trip latency using a Raspberry pi 5 running Neural Amp Modeler plus a few other LV2 plugins, in Linux. World record?

https://preview.redd.it/3a3prz1ou10h1.png?width=4032&format=png&auto=webp&s=d1e497ced4406b57fd16db5a1197f1b366a0594f

Will add more detail soon, achieved on a Pi 5 running dietpi and a bunch of mods to the preempt_rt kernel. 3.5ms using a scarlett as an input, 1.9ms using direct i2s AD/DA (PCM5102A/PCM1808). it was a pain lmfao but damn it's fun. Currently working on getting the noise floor down, very noisy since i can't get a good clock for the output 1808.

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u/NiisanHP — 13 days ago

I've just started using NAM on ableton and im getting no input signal at all, but only in NAM, ableton picks up my guitar fine, its just a NAM issue. Any help?

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u/GorkedYT — 15 days ago