# Neural Amp Modeler

Neural network emulator for guitar amplifiers.

Repository: https://github.com/sdatkinson/neural-amp-modeler
Canonical: https://ross.abutalabs.com/products/neural-amp-modeler
Language: Python
License: MIT
License Family: permissive
Last push: 2026-08-23T01:38:28+00:00

## Health v2 (maintenance only)
Score: 90/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 74, longevity 100
- inputs: {"age_days": 2800, "days_push": 11, "days_rel": 92, "gap_med": 79.0, "n_releases_24m": 7}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2986, forks 275 (observed 2026-08-28T04:07:34.005175+00:00)

## What it is
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
- artifact type: library
- maturity: active
- function: machine-learning, deep-learning, audio-processing
- domain: machine-learning, deep-learning
- platform: python, cross-platform
- tags: neural-network, guitar-amp, audio-emulation, amp-modeling, plugin, vst, music-production, audio, desktop

## Member repositories
- sdatkinson/neural-amp-modeler (main) score 90
- sdatkinson/NeuralAmpModelerPlugin (plugin) score 90

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:34.005175+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:31:25.365761+00:00, confidence not recorded.
  - readme: https://github.com/sdatkinson/neural-amp-modeler (fetched 2026-08-28T04:07:34.005175+00:00, sha 1795c8b5b2c4)
- Data as of 2026-08-30T08:39:29.467469+00:00.