LibreAI / Audio / GPA
// audio · AutoArk/GPA

GPA

GPA ist ein Open-Source-Projekt aus der Kategorie Audio von AutoArk (AutoArk/GPA auf GitHub). Es hat 3.109 Sterne auf GitHub und 206 Forks, wird unter der Lizenz Apache-2.0 veröffentlicht und wurde zuletzt am 25. Mai 2026 auf GitHub aktualisiert.

GPA — one tiny model that does ASR, TTS and voice conversion (General Purpose Audio).

★ 3,1 Tsd. Sterne⑂ 206 ForksApache-2.0aktualisiert Mai 2026
▦ Visual — das README dieses Projekts enthält keinen einbettbaren Screenshot,
darum hier ein Platzhalter. Die Anleitung unten ist trotzdem vollständig.
// projektdaten

Projektdaten

Repository
AutoArk/GPA
GitHub-Sterne
3.109
Forks
206
Lizenz
Apache-2.0
Zuletzt auf GitHub aktualisiert
25. Mai 2026
Kategorie
Audio
Eintragstyp
Vollständige Installationsanleitung
Offizielle Website
Official site
// so funktioniert es

So funktioniert es

  1. Clarify your goal

    Decide the first concrete outcome you want from it, so you can pick the right example, template or mode instead of exploring everything at once.

  2. Get the project

    Clone the repository (or install the published package) and skim its README quick start for the requirements for your platform.

  3. Install and configure

    Run the documented install step and set any required configuration — such as provider keys, data sources or local services — before the first run.

  4. Run your first task

    Execute the smallest documented example end to end, confirm the output is what you expected, then adapt it to your real data or workflow.

// funktionen

Warum es so beliebt ist

One model, three tasks

ASR, TTS and voice conversion in a single tiny model instead of three separate systems.

GPA-v1.5 mainline

Native inference and training pipelines with published TTS/ASR evaluation tables.

Edge-ready voice-cloning TTS

GPA-TTS ships INT8/FP16/FP32 and INT4 ONNX variants for constrained hardware.

ONNX Runtime interfaces

CLI, API and UI around the v1.5 ONNX runtime for easy integration.

Open releases

GPA-0.3B-preview and GPA-v1.5 checkpoints are released, with a public roadmap (deployment recipes and a native VC path are listed as next steps).

Unified architecture

An LLM-based design for both audio generation and understanding.

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// selbst ausführen

Führe es selbst aus

  1. Clone the repository

    Get the source so you can inspect, configure and run it locally.

    git clone https://github.com/AutoArk/GPA.git
    cd GPA
  2. Get GPA

    Clone the repo and follow the GPA-v1.5 (GPA_1.5/) or GPA-TTS (GPA_TTS/) folder's own README for environment setup, checkpoints and inference commands.

    git clone https://github.com/AutoArk/GPA.git
    cd GPA  # see GPA_1.5/README.md or GPA_TTS/README.md for the exact commands
  3. Run inference

    Use the v1.5 ONNX Runtime CLI/API/UI or the GPA-TTS runtime as documented in their sub-READMEs.

    # see README for the exact command in GPA_1.5/ or GPA_TTS/
// anwendungsfälle

Was du damit bauen kannst

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// häufige fragen

Häufige Fragen

Who maintains GPA?

It is maintained by AutoArk on GitHub (AutoArk/GPA), where the source, issues and releases live.

Is it free to use?

Yes — it is free and open source under Apache-2.0, which permits use, modification and commercial redistribution, with licence/notice retention.

Does it need a paid API key?

No — GPA runs locally from released checkpoints; there is no hosted API key involved.

How does it compare to separate specialist models for ASR, TTS and VC?

Compared with separate specialist models for ASR, TTS and VC, GPA's distinguishing focus is: gPA — one tiny model that does ASR, TTS and voice conversion (General Purpose Audio). Pick it when that focus matches your need; the alternative may suit you better if its broader or different scope is the priority.

How do I get started?

Clone https://github.com/AutoArk/GPA (or install its published package), follow the README quick start to install and configure it, then run the smallest documented example — the Run section on this page mirrors those steps.

// weiter entdecken

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// alternativen

Alternativen im Bereich Audio

Die anderen Projekte der Kategorie Audio mit den meisten Sternen im LibreAI-Katalog — die realistische Auswahl, falls GPA nicht das Richtige ist.

// mehr in audio

Mehr in Audio

Verwandte Projekte der Kategorie Audio im Katalog, die GPA bei den Sternen am nächsten stehen — zum Weiterstöbern auf beiden Seiten.

Hol dir GPA

Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.