LLaMA-Mesh
Zhengyi's LLaMA-Mesh is a chat model. LLaMA-Mesh is an open-weights chat model.
by Zhengyi
Best for
Ways to use LLaMA-Mesh in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your Zhengyi API key. osFoundry discovers LLaMA-Mesh 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
LLaMA-Mesh 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.
LLaMA-Mesh vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about LLaMA-Mesh
Is LLaMA-Mesh free to use?
LLaMA-Mesh 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 LLaMA-Mesh 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 LLaMA-Mesh locally?
Yes. LLaMA-Mesh is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is LLaMA-Mesh best at?
LLaMA-Mesh is well-suited to text to 3d.
How do I use LLaMA-Mesh in osFoundry?
Paste your Zhengyi API key in the key dialog (or deploy the open weights for self-hostable models), assign LLaMA-Mesh to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by Zhengyi on November 17, 2024. Source: https://huggingface.co/Zhengyi/LLaMA-Mesh