MedTE-cl15-step-8000
Built by MohammadKhodadad, MedTE-cl15-step-8000 is an embedding model. MedTE-cl15-step-8000 is an open-weights embed model.
by MohammadKhodadad
Best for
Ways to use MedTE-cl15-step-8000 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your MohammadKhodadad API key. osFoundry discovers MedTE-cl15-step-8000 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
MedTE-cl15-step-8000 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.
MedTE-cl15-step-8000 vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about MedTE-cl15-step-8000
Is MedTE-cl15-step-8000 free to use?
MedTE-cl15-step-8000 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 MedTE-cl15-step-8000 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 MedTE-cl15-step-8000 locally?
Yes. MedTE-cl15-step-8000 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is MedTE-cl15-step-8000 best at?
MedTE-cl15-step-8000 is well-suited to feature extraction.
How do I use MedTE-cl15-step-8000 in osFoundry?
Paste your MohammadKhodadad API key in the key dialog (or deploy the open weights for self-hostable models), assign MedTE-cl15-step-8000 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by MohammadKhodadad on May 3, 2025. Source: https://huggingface.co/MohammadKhodadad/MedTE-cl15-step-8000