TimeMoE-200M
TimeMoE-200M (Maple728, 2024) is an chat model. TimeMoE-200M is an open-weights chat model.
by Maple728
Best for
Ways to use TimeMoE-200M in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your Maple728 API key. osFoundry discovers TimeMoE-200M 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
TimeMoE-200M 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.
TimeMoE-200M vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about TimeMoE-200M
Is TimeMoE-200M free to use?
TimeMoE-200M 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 TimeMoE-200M 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 TimeMoE-200M locally?
Yes. TimeMoE-200M is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is TimeMoE-200M best at?
TimeMoE-200M is well-suited to time series forecasting.
How do I use TimeMoE-200M in osFoundry?
Paste your Maple728 API key in the key dialog (or deploy the open weights for self-hostable models), assign TimeMoE-200M to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by Maple728 on September 21, 2024. Source: https://huggingface.co/Maple728/TimeMoE-200M