NADI2024-baseline
AMR-KELEG's NADI2024-baseline is a chat model. NADI2024-baseline is an open-weights chat model.
by AMR-KELEG
Best for
Ways to use NADI2024-baseline in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your AMR-KELEG API key. osFoundry discovers NADI2024-baseline 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
NADI2024-baseline 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.
NADI2024-baseline vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about NADI2024-baseline
Is NADI2024-baseline free to use?
NADI2024-baseline 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 NADI2024-baseline 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 NADI2024-baseline locally?
Yes. NADI2024-baseline is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is NADI2024-baseline best at?
NADI2024-baseline is well-suited to text classification.
How do I use NADI2024-baseline in osFoundry?
Paste your AMR-KELEG API key in the key dialog (or deploy the open weights for self-hostable models), assign NADI2024-baseline to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by AMR-KELEG on June 7, 2024. Source: https://huggingface.co/AMR-KELEG/NADI2024-baseline