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ToobAmp v1.1.63 aarch64

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Robin E. R. Davies
2025-07-01 01:39:42 -04:00
parent e092aed47b
commit c9204f7636
28 changed files with 49 additions and 39 deletions
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lv2/aarch64/ToobAmp.lv2/ToobNeuralAmpModeler.ttl
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@@ -61,33 +61,43 @@ toobNam:eqGroup
doap:license <https://rerdavies.github.io/pipedal/LicenseToobAmp> ;
doap:maintainer <http://two-play.com/rerdavies#me> ;
lv2:minorVersion 0 ;
lv2:microVersion 62 ;
lv2:microVersion 63 ;
rdfs:comment """
A port of Steven Atkinson's Neural Amp Modeler to LV2.
TooB Neural Amp Modeler uses uploadable .nam model files. Download .nam files from http://tonehunt.org, and then load them into TooB Neural Amp Modeler.
TooB Neural Amp Modeler uses uploadable .nam model files. Download .nam model files from http://tone3000.com, and then load them into TooB Neural Amp Modeler.
If you are using TooB Neural Amp Modeler from PiPedal, download the model files to the system on which you are running the client. You must then
upload the file to the PiPedal server. Click on the "Model" control and then search for the Upload button in the file browser. Once uploaded to the server,
you can then select the uploaded file in the browser directly.
The TONE3000 website contains a huge collection of community-developed amp models that can be used with TooB Neural Amp Modeler. You can also use .nam models from
other sources. Using TONE3000 models with TooB Neural Amp Modeler is a two-step process. First, download model files to your local system using a
web browser. Then upload the model files to the PiPedal server using the PiPedal web interface. You can find an "Upload" button in
the file browser when you click on the "Model" control in the PiPedal web interface.
If you are not using PiPedal, just click on the Model control, and use the file browser to select the .nam file on your local system.
TooB Neural Amp Modeler supports a much wider range of amp models than ToobML, but usually uses much more CPU.
If you are not using PiPedal, just click on the Model control, and use the file browser to select the .nam file directly on your local system.
TooB Neural Amp Modeler supports a much wider range of amp models than ToobML, but usually uses more CPU.
You will need at least a Pi 4 to use Toob Neural Amp Modeler, and you may need to increase your audio buffer sizes to prevent overruns.
If you are having trouble with CPU usage, tonehunt.org does contain some smaller amp models. Search for the "feather" tag to find
models that use less CPU.
If you are having trouble with CPU usage, tone3000.com does contain some smaller amp models. Search for the "feather" tag to find
models that use less CPU. Generally, you can use up to three NAM models at once in a given preset on a Pi 4, and up to 5 MAM models
simultaneously on a Pi 5. N100 micro PCs could presumably do even better. However, exact CPU use varies depending on the complexity of the amp models you are using.
Users have reported success using NAM on Raspberry Pi 3 devices, but this is not recommended (or really supported), as CPU usage is very high on a Raspberry Pi 3.
If you are interested in profiling your own amps and effect pedals, please visit https://www.tone3000.com/capture
If you are interested in building your own amp models, please visit https://www.neuralampmodeler.com/
TooB Neural Amp Modeler contains code optimizations that allow use of a third model on Raspberry PI 4 devices. These optimizations
were offered to the upstream NAM project, but we recommended that they not be merged into upstream sources, because they
significantly affect maintainability of the codebase. and the performance increase they provide (about 30%) is really only
relevant on Raspberry PI 4-class devices. If you are interested in these optimizations, they have been published in ToobAmp
project sources on GitHub.
TooB Neural Amp Modeler uses code from the NeuralAmp Modeler Core project. The TooB Team wishes to express gratitude to Steven Atkinson for
making this extraordinary technology available as open-source code.
TooB Neural Amp Modeler uses code from the NeuralAmp Modeler Core project (https://www.neuralampmodeler.com/). The TooB team wishes
to express gratitude to Steven Atkinson for making this revolutionary technology available as open-source code.
Code from the the NeuralAmpModelerCore project (https://github.com/sdatkinson/NeuralAmpModelerCore) is provided under the following license.
Code from the the NeuralAmpModelerCore project (https://github.com/sdatkinson/NeuralAmpModelerCore) is provided
under the following license.
MIT License
Copyright (c) 2023 Steven Atkinson
Copyright (c) 2025 Steven Atkinson
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal