xlm-r-parla
xlm-r-parla (classla, 2023) is an chat model. xlm-r-parla is an open-weights chat model.
by classla
Best for
Ways to use xlm-r-parla in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your classla API key. osFoundry discovers xlm-r-parla 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
xlm-r-parla 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.
xlm-r-parla vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about xlm-r-parla
Is xlm-r-parla free to use?
xlm-r-parla 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 xlm-r-parla 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 xlm-r-parla locally?
Yes. xlm-r-parla is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is xlm-r-parla best at?
xlm-r-parla is well-suited to fill mask.
How do I use xlm-r-parla in osFoundry?
Paste your classla API key in the key dialog (or deploy the open weights for self-hostable models), assign xlm-r-parla to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by classla on September 5, 2023. Source: https://huggingface.co/classla/xlm-r-parla