bge-m3_en_ru
bge-m3_en_ru (BorisTM, 2024) is an embedding model. bge-m3_en_ru is an open-weights embed model.
by BorisTM
Best for
Ways to use bge-m3_en_ru in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your BorisTM API key. osFoundry discovers bge-m3_en_ru 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
bge-m3_en_ru 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.
bge-m3_en_ru vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about bge-m3_en_ru
Is bge-m3_en_ru free to use?
bge-m3_en_ru 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 bge-m3_en_ru 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 bge-m3_en_ru locally?
Yes. bge-m3_en_ru is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is bge-m3_en_ru best at?
bge-m3_en_ru is well-suited to sentence similarity.
How do I use bge-m3_en_ru in osFoundry?
Paste your BorisTM API key in the key dialog (or deploy the open weights for self-hostable models), assign bge-m3_en_ru to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by BorisTM on June 14, 2024. Source: https://huggingface.co/BorisTM/bge-m3_en_ru