readabert-en
readabert-en (tareknaous, 2024) is an chat model. readabert-en is an open-weights chat model.
by tareknaous
Best for
Ways to use readabert-en in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your tareknaous API key. osFoundry discovers readabert-en 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
readabert-en 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.
readabert-en vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about readabert-en
Is readabert-en free to use?
readabert-en 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 readabert-en 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 readabert-en locally?
Yes. readabert-en is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is readabert-en best at?
readabert-en is well-suited to text classification.
How do I use readabert-en in osFoundry?
Paste your tareknaous API key in the key dialog (or deploy the open weights for self-hostable models), assign readabert-en to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by tareknaous on February 17, 2024. Source: https://huggingface.co/tareknaous/readabert-en