Neural Amp Modeler

Health v2 · maintenance only

Adoption not part of the score

2986 stars · 275 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Neural Amp Modeler (NAM) is a Python project that trains neural network models to emulate guitar amplifiers and exports them as .nam files. A companion plugin repo provides real-time playback of these models as a standalone app or audio plugin.

Use cases

• emulate guitar amplifiers with neural networks
• train amp models from audio captures
• create .nam files for amp simulation
• run neural amp models in real time as a VST plugin
• capture and clone the tone of a physical amp
• build digital amp profiles for music production

When to choose

• you want to model a guitar amp or pedal from recorded audio
• you need a free, open-source alternative to commercial amp-capture tools
• you want to train custom amp models in Python and use them in a DAW

When to avoid

• you need general-purpose audio processing rather than amp modeling
• you want a ready-made amp simulator without training your own models
• you lack audio capture gear or training data

Facets

library · maturity active

machine-learning deep-learning audio-processing machine-learning deep-learning python cross-platform neural-network guitar-amp audio-emulation amp-modeling plugin vst music-production audio desktop

Member repositories

For agents

markdown · JSON · MCP: product_card(name="sdatkinson/neural-amp-modeler")