lam-tts-jp-80m
tsukemono's lam-tts-jp-80m is a speech-and-audio model. lam-tts-jp-80m is an open-weights audio model.
by tsukemono
Best for
Ways to use lam-tts-jp-80m in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your tsukemono API key. osFoundry discovers lam-tts-jp-80m automatically — assign it to a Maestro role (router, direct, orchestrator, or fallback) in the Pipeline tab and it is live in every chat. Your key, your provider account — no token markup.
Deploy a dedicated endpoint
lam-tts-jp-80m is open-weights — run it locally for free, or deploy a dedicated GPU endpoint in your workspace for reserved capacity with no rate limits.
Use it in a Room App
Room Apps declare AI features in their manifest, then call them with invokeAI:
import { invokeAI } from '@osfoundry/app-sdk'
// 'summarize' is an AI feature declared in your app manifest.
const result = await invokeAI('summarize', userText)
Call it from your own apps
Once a model is wired into your workspace you can host it as an API and reach it from your own services, scripts, or CI — outside osFoundry.
lam-tts-jp-80m vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about lam-tts-jp-80m
Is lam-tts-jp-80m free to use?
lam-tts-jp-80m is free to run locally on your own hardware. Hosted access through osFoundry is metered (input Free (local), output Free (local)). You can switch between local and hosted at any time.
Can I use lam-tts-jp-80m commercially?
Commercial use is allowed with conditions. Licence terms not specified — verify the upstream model card before commercial use. Check upstream documentation.
Can I run lam-tts-jp-80m locally?
Yes. lam-tts-jp-80m is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is lam-tts-jp-80m best at?
lam-tts-jp-80m is well-suited to text to speech.
How do I use lam-tts-jp-80m in osFoundry?
Paste your tsukemono API key in the key dialog (or deploy the open weights for self-hostable models), assign lam-tts-jp-80m to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by tsukemono on March 20, 2026. Source: https://huggingface.co/tsukemono/lam-tts-jp-80m