baseline_mean
baseline_mean (jsprin18, 2026) is an chat model. baseline_mean is an open-weights chat model.
by jsprin18
Best for
- low-latency chat and routing
- request routing and triage
- text classification
Ways to use baseline_mean in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your jsprin18 API key. osFoundry discovers baseline_mean 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
baseline_mean 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.
baseline_mean vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about baseline_mean
Is baseline_mean free to use?
baseline_mean 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 baseline_mean 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 baseline_mean locally?
Yes. baseline_mean is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is baseline_mean best at?
baseline_mean is well-suited to low-latency chat and routing, request routing and triage, text classification.
How do I use baseline_mean in osFoundry?
Paste your jsprin18 API key in the key dialog (or deploy the open weights for self-hostable models), assign baseline_mean to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by jsprin18 on April 27, 2026. Source: https://huggingface.co/jsprin18/baseline_mean