m2m_arranger
LongshenOu's m2m_arranger is a chat model. m2m_arranger is an open-weights chat model.
by LongshenOu
Best for
Ways to use m2m_arranger in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your LongshenOu API key. osFoundry discovers m2m_arranger 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
m2m_arranger 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.
m2m_arranger vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about m2m_arranger
Is m2m_arranger free to use?
m2m_arranger 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 m2m_arranger 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 m2m_arranger locally?
Yes. m2m_arranger is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is m2m_arranger best at?
m2m_arranger is well-suited to text generation.
How do I use m2m_arranger in osFoundry?
Paste your LongshenOu API key in the key dialog (or deploy the open weights for self-hostable models), assign m2m_arranger to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by LongshenOu on July 15, 2024. Source: https://huggingface.co/LongshenOu/m2m_arranger