LaBSE-ru-turbo
sergeyzh's LaBSE-ru-turbo is a embedding model. LaBSE-ru-turbo is an open-weights embed model.
by sergeyzh
Best for
Ways to use LaBSE-ru-turbo in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your sergeyzh API key. osFoundry discovers LaBSE-ru-turbo 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
LaBSE-ru-turbo 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.
LaBSE-ru-turbo vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about LaBSE-ru-turbo
Is LaBSE-ru-turbo free to use?
LaBSE-ru-turbo 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 LaBSE-ru-turbo 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 LaBSE-ru-turbo locally?
Yes. LaBSE-ru-turbo is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is LaBSE-ru-turbo best at?
LaBSE-ru-turbo is well-suited to sentence similarity.
How do I use LaBSE-ru-turbo in osFoundry?
Paste your sergeyzh API key in the key dialog (or deploy the open weights for self-hostable models), assign LaBSE-ru-turbo to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by sergeyzh on June 27, 2024. Source: https://huggingface.co/sergeyzh/LaBSE-ru-turbo