passage-ranker.mango
passage-ranker.mango is a chat model from sinequa, released July 10, 2023. passage-ranker.mango is an open-weights chat model.
by sinequa
Best for
Ways to use passage-ranker.mango in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your sinequa API key. osFoundry discovers passage-ranker.mango 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
passage-ranker.mango 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.
passage-ranker.mango vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about passage-ranker.mango
Is passage-ranker.mango free to use?
passage-ranker.mango 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 passage-ranker.mango 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 passage-ranker.mango locally?
Yes. passage-ranker.mango is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is passage-ranker.mango best at?
passage-ranker.mango is well-suited to text classification.
How do I use passage-ranker.mango in osFoundry?
Paste your sinequa API key in the key dialog (or deploy the open weights for self-hostable models), assign passage-ranker.mango to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by sinequa on July 10, 2023. Source: https://huggingface.co/sinequa/passage-ranker.mango