NAMFORUM Sysop: Created page

2026-09-01T06:14:01Z

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= Resources =

This page collects useful resources for '''capture, profiling, neural audio modeling, model training, playback, and model sharing'''.

Where possible, NAMFORUM Wiki favors:

* Official documentation
* Primary project sources
* Original developer repositories
* Official training tools
* Established model libraries

Third-party resources can be added when they provide substantial technical or practical value.

Because capture technology develops rapidly, software versions, hardware support, model counts, and online services may change.

__TOC__

== Neural Amp Modeler ==

=== Official NAM website ===

'''Neural Amp Modeler'''

[https://www.neuralampmodeler.com/ neuralampmodeler.com]

The primary website for the Neural Amp Modeler project.

It provides access to:

* NAM software
* Training resources
* Project information
* Developer resources
* Community links

See [[Neural Amp Modeler]].

=== NAM user resources ===

[https://www.neuralampmodeler.com/users NAM for Users]

The official starting point for NAM users.

It includes links for:

* NAM model creation
* Google Colab training
* Local training
* Standardized training files
* Gateway
* Model sharing

=== NAM documentation ===

[https://neural-amp-modeler.readthedocs.io/ Neural Amp Modeler documentation]

Technical documentation for the NAM training system and model format.

Important sections include:

* Training
* Local GUI
* Calibration
* Model file specification
* Metadata
* Development information

See:

* [[Training a NAM Model]]
* [[NAM Model File Format]]
* [[Gain Staging and Calibration]]

=== NAM source code ===

[https://www.neuralampmodeler.com/the-code NAM — The Code]

The NAM project maintains separate open-source components for:

* Trainer
* Core DSP
* Plugin

These components make it possible to study and implement NAM training and playback independently.

=== Gateway ===

'''Gateway''' is the official NAM model player linked from the NAM user resources.

Use the current download links at:

[https://www.neuralampmodeler.com/users NAM for Users]

Gateway provides desktop playback of NAM snapshot models.

See [[NAM Playback]].

=== TONE3000 ===

[https://tone3000.com/ TONE3000]

TONE3000 is a community-organized online model library and training service used extensively by the NAM community.

The official NAM website directs users to TONE3000 for model sharing.

TONE3000 provides:

* NAM model discovery
* Creator profiles
* Model sharing
* Online training
* Search and organization

Because online services evolve rapidly, consult TONE3000 directly for current supported model types and training features.

== TONEX ==

=== Official TONEX website ===

[https://www.ikmultimedia.com/products/tonex/ IK Multimedia TONEX]

The primary source for the TONEX ecosystem.

TONEX includes:

* TONEX Player
* TONEX Modeler
* TONEX Editor
* ToneNET
* TONEX hardware
* Mobile integration

See [[TONEX]].

=== TONEX Modeler ===

TONEX Modeler is IK Multimedia's dedicated application for creating Tone Models.

Current information is available through:

[https://www.ikmultimedia.com/products/tonex/ TONEX]

TONEX Modeler supports modeling of equipment including:

* Amplifiers
* Cabinets
* Combos
* Overdrive
* Distortion
* Fuzz
* EQ
* Boost
* Complete compatible rigs

=== ToneNET ===

[https://www.tone.net/tonex ToneNET]

IK Multimedia's online service for discovering and sharing TONEX content.

ToneNET provides access to community-created Tone Models and presets.

Exact library counts change continuously and should not be treated as permanent specifications.

=== TONEX hardware ===

Current TONEX hardware information is available through:

[https://www.ikmultimedia.com/products/tonex/ TONEX]

The ecosystem includes dedicated hardware for portable and live Tone Model playback.

Consult current IK Multimedia documentation for compatibility and feature differences between devices.

== Kemper Profiling ==

=== Official Kemper website ===

[https://www.kemper-amps.com/ Kemper]

The primary source for Kemper PROFILER hardware, software, documentation, and current profiling technology.

See [[Kemper Profiling]].

=== PROFILER information ===

[https://www.kemper-amps.com/profiler/overview Kemper PROFILER]

Information about the current PROFILER ecosystem, including:

* PROFILING
* Liquid Profiling
* PROFILING 2.0
* PROFILER hardware
* Effects
* Rig management

=== Rig Manager ===

'''Rig Manager''' is Kemper's software for managing PROFILER content.

It provides access to:

* Rigs
* Presets
* PROFILER management
* Rig Exchange

Current downloads and documentation are available through the Kemper website.

=== Rig Exchange ===

'''Rig Exchange''' is Kemper's community library for shared Rigs.

Access is available through Rig Manager and the Kemper ecosystem.

Because the library is continuously changing, exact Rig counts should be treated as time-sensitive.

=== Kemper documentation ===

Current manuals and support documentation are available through:

[https://www.kemper-amps.com/downloads Kemper Downloads]

For technical questions, current Kemper documentation should take precedence over older tutorials or forum posts.

== Neural DSP Neural Capture ==

=== Quad Cortex ===

[https://neuraldsp.com/quad-cortex Neural DSP Quad Cortex]

Official information about Neural DSP's Quad Cortex platform.

Quad Cortex combines:

* Neural Capture
* Algorithmic amplifier modeling
* Cabinet processing
* Effects
* Routing
* Hardware control

See [[Neural Capture]].

=== Quad Cortex manual ===

[https://neuraldsp.com/manual/quad-cortex Quad Cortex User Manual]

The primary technical reference for:

* Neural Capture
* Cortex routing
* Connections
* Capture procedures
* Presets
* Device operation

=== Cortex Control ===

[https://neuraldsp.com/cortex-control Cortex Control]

Neural DSP's desktop application for Cortex hardware.

Cortex Control also participates in the Neural Capture V2 creation workflow.

=== Cortex Cloud ===

'''Cortex Cloud''' is Neural DSP's online system for Cortex content.

It is used for:

* Neural Capture sharing
* Content discovery
* User libraries
* Neural Capture V2 cloud processing

Access is provided through Neural DSP's Cortex ecosystem.

=== Neural Capture V2 ===

Current information about Neural Capture V2 should be obtained directly from Neural DSP.

See:

[https://neuraldsp.com/news/introducing-neural-capture-version-2 Introducing Neural Capture Version 2]

See also [[Neural Capture]].

== Line 6 Proxy ==

=== Helix Stadium ===

[https://line6.com/helix-stadium/ Helix Stadium]

The primary Line 6 product resource for the Helix Stadium platform.

Stadium combines:

* Line 6 amplifier modeling
* Agoura modeling
* Proxy Clones
* Cabinet processing
* Effects
* Advanced routing

See [[Line 6 Proxy]].

=== Proxy Cloning documentation ===

[https://manuals.line6.com/en/helix-stadium/live/clones Proxy Cloning]

The current Line 6 documentation for creating and using Proxy Clones.

It covers:

* Amp+Cab Clones
* Amp Clones
* Preamp Clones
* Distortion Clones
* Connections
* Level setup
* Cloud processing
* Clone management

=== Helix Stadium manual ===

[https://manuals.line6.com/en/helix-stadium/live Helix Stadium Owner's Manual]

The primary technical reference for Stadium hardware and software operation.

=== CustomTone ===

[https://line6.com/customtone/ Line 6 CustomTone]

Line 6's community service for sharing compatible presets and Proxy Clones.

== Open capture technologies ==

Open-source capture technology extends beyond NAM.

See [[Open Capture Technologies]].

=== AIDA-X ===

[https://github.com/AidaDSP/AIDA-X AIDA-X]

AIDA-X is an open-source Amp Model player developed by Aida DSP.

The project supports neural models of:

* Amplifiers
* Cabinets
* Drive pedals
* Fuzz
* Boost
* EQ
* Combined signal chains

AIDA-X uses RTNeural for neural-network inference and provides desktop and embedded implementations.

=== GuitarML Proteus ===

[https://github.com/GuitarML/Proteus GuitarML Proteus]

Proteus is an open-source guitar amplifier and pedal capture system.

It supports:

* Snapshot models
* Conditioned models
* Amplifier captures
* Pedal captures
* Plugin captures
* Combined rigs

The project includes a capture utility and training workflow.

=== GuitarML NeuralPi ===

[https://github.com/GuitarML/NeuralPi NeuralPi]

An open-source GuitarML project exploring neural guitar processing and embedded model playback.

=== GuitarML ToneLibrary ===

[https://github.com/GuitarML/ToneLibrary GuitarML ToneLibrary]

A library of models for GuitarML projects.

Model compatibility depends on the neural architecture and intended player.

Do not assume that every GuitarML JSON model is compatible with every GuitarML application.

=== SmartGuitarAmp ===

[https://github.com/GuitarML/SmartGuitarAmp SmartGuitarAmp]

An earlier GuitarML neural amplifier project using WaveNet-style modeling.

It is useful both historically and technically for understanding the development of open neural guitar modeling.

== Model libraries ==

Capture technology becomes substantially more useful when models can be shared.

Major sharing ecosystems include:

{| class="wikitable"
! Platform
! Model library / sharing service
|-
| [[Neural Amp Modeler]]
| [https://tone3000.com/ TONE3000]
|-
| [[TONEX]]
| [https://www.tone.net/tonex ToneNET]
|-
| [[Kemper Profiling]]
| Rig Exchange
|-
| [[Neural Capture]]
| Cortex Cloud
|-
| [[Line 6 Proxy]]
| [https://line6.com/customtone/ CustomTone]
|-
| GuitarML
| [https://github.com/GuitarML/ToneLibrary ToneLibrary]
|}

Availability, account requirements, and supported model types can change.

== Training resources ==

Before creating a model, see:

* [[Getting Started with Capture Technology]]
* [[Capture Signal Chain]]
* [[Gain Staging and Calibration]]
* [[Reamping for Capture]]
* [[Creating a Capture]]
* [[Capture Types]]
* [[Cabinets and IRs]]
* [[Troubleshooting Captures]]

For NAM specifically:

* [[Training a NAM Model]]
* [[NAM Model File Format]]
* [[NAM A2 Architecture]]

== Capture hardware ==

Capture workflows may require additional equipment beyond the model-training software.

Depending on the target, this can include:

* Audio interface
* Reamp box
* DI box
* Load box
* Microphone
* Microphone preamp
* Appropriate cables
* Measurement equipment

No single hardware configuration is required for every capture.

The correct signal chain depends on what is being modeled.

See [[Capture Signal Chain]].

== Reamping resources ==

Reamping is fundamental to many computer-based capture workflows.

See:

* [[Reamping for Capture]]
* [[Gain Staging and Calibration]]
* [[Capture Signal Chain]]

The objective is to send a repeatable training signal through physical equipment while maintaining appropriate levels and connections.

== Load boxes ==

Direct amplifier capture generally requires an appropriate load when working from a power-amplifier speaker output.

A load box may provide:

* Safe amplifier load
* Line-level output
* Attenuation
* Reactive loading
* Cabinet simulation
* IR processing

When making a direct amplifier capture, cabinet or speaker simulation in the load box should normally be disabled unless intentionally included in the model.

'''Never connect an amplifier speaker output directly to an ordinary audio-interface or capture-device input.'''

== Cabinet impulse responses ==

Cabinet IRs are widely used with direct amplifier captures.

An IR can represent the approximately linear response of a:

'''speaker + cabinet + microphone'''

chain.

Useful background is available at:

[[Cabinets and IRs]]

When downloading an IR, check:

* Sample rate
* File format
* Length
* Microphone
* Speaker
* Cabinet
* Microphone position

where that information is available.

== Technical research ==

Capture technology overlaps with research fields including:

* Nonlinear system identification
* Neural audio processing
* Deep learning
* Recurrent neural networks
* Temporal convolutional networks
* Real-time neural inference
* Differentiable digital signal processing

Academic papers can provide valuable information about the architectures and evaluation methods behind modern capture systems.

However, research terminology and product terminology are not always equivalent.

A commercial feature described as a ''capture'', ''profile'', or ''clone'' should not be assumed to use a particular published neural architecture unless the developer has documented that architecture.

== GitHub ==

[https://github.com/ GitHub]

Many open-source audio-modeling projects publish their source code and technical documentation on GitHub.

Useful repositories include:

* [https://github.com/AidaDSP/AIDA-X AIDA-X]
* [https://github.com/GuitarML/Proteus GuitarML Proteus]
* [https://github.com/GuitarML/NeuralPi GuitarML NeuralPi]
* [https://github.com/GuitarML/ToneLibrary GuitarML ToneLibrary]

NAM's current source-code links are maintained at:

[https://www.neuralampmodeler.com/the-code NAM — The Code]

== Evaluating third-party information ==

Capture technology changes quickly.

Before relying on a tutorial, video, forum post, or social-media comment, check:

* Publication date
* Software version
* Hardware version
* Model architecture
* Whether the information applies to the current release
* Whether the author actually performed the described procedure
* Whether a primary source confirms the claim

Older information can remain useful, but it may describe software or workflows that have since changed substantially.

== Primary sources ==

For factual Wiki articles, NAMFORUM should prefer primary sources where practical.

Examples include:

* Developer documentation
* Official manuals
* Source-code repositories
* Release notes
* Technical specifications
* Original research papers
* Statements from project developers

Community discussion remains valuable for:

* Practical experience
* Troubleshooting
* Comparisons
* Workarounds
* Experiments
* Independent testing

The two forms of information serve different purposes.

== Contributing resources ==

Useful resources may be suggested through NAMFORUM.

Good candidates include:

* Official documentation
* Technical papers
* Open-source projects
* Training tools
* Capture utilities
* Model libraries
* Technical measurements
* Well-documented tutorials
* Long-term archival resources

A resource should provide meaningful value rather than simply being a promotional link.

== NAMFORUM ==

'''NAMFORUM''' is an independent discussion community covering Neural Amp Modeling technology and other capture technology.

[https://namforum.com/ Visit NAMFORUM]

The forum is the appropriate place to:

* Ask questions
* Discuss equipment
* Share experience
* Compare capture systems
* Discuss training methods
* Troubleshoot models
* Suggest Wiki improvements
* Discuss new capture technologies

The Wiki is intended to preserve established technical information that emerges from documentation, research, and community experience.

== See also ==

* [[Capture Technologies]]
* [[Glossary]]
* [[Getting Started with Capture Technology]]
* [[Capture Signal Chain]]
* [[Gain Staging and Calibration]]
* [[Reamping for Capture]]
* [[Creating a Capture]]
* [[Capture Types]]
* [[Cabinets and IRs]]
* [[Troubleshooting Captures]]
* [[Neural Amp Modeler]]
* [[TONEX]]
* [[Kemper Profiling]]
* [[Neural Capture]]
* [[Line 6 Proxy]]
* [[Open Capture Technologies]]

[[Category:Resources]]
[[Category:Capture technology]]
[[Category:Reference]]

Resources - Revision history

NAMFORUM Sysop: Created page