# Neural Amp Modeler Neural Amp Modeler (NAM) is a free, open-source project by Steven Atkinson. It uses deep learning to build models ("captures") of guitar amps and pedals, with state-of-the-art accuracy. It's now the de facto open standard for amp captures. Other software loads NAM models (e.g. [[Tonocracy]]), and hardware makers like Darkglass, Two Notes, Hotone, Valeton, Sonicake and MOD Audio build it into their products. ## Components - **Plugins** (Windows and macOS installers): - **Gateway**: loads snapshot models of real gear - **ParametricOD**: a concept overdrive plugin - **Trainer**: build your own models by reamping your gear with standardized test files - Online, in the browser via Google Colab (nothing to install) - Locally, with the Python trainer from PyPI - **Models**: TONE3000 is the community library for finding and sharing NAM models ## References - https://www.neuralampmodeler.com/ - https://www.neuralampmodeler.com/users ## Related - [[Tonocracy]] - [[Guitarix]] - [[Reaper]]