nemo_baseline_models
Built by chime-dasr, nemo_baseline_models is an chat model. nemo_baseline_models is an open-weights chat model.
by chime-dasr
Best for
- low-latency chat and routing
- request routing and triage
- text classification
Ways to use nemo_baseline_models in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your chime-dasr API key. osFoundry discovers nemo_baseline_models 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
nemo_baseline_models 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.
nemo_baseline_models vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about nemo_baseline_models
Is nemo_baseline_models free to use?
nemo_baseline_models 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 nemo_baseline_models 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 nemo_baseline_models locally?
Yes. nemo_baseline_models is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is nemo_baseline_models best at?
nemo_baseline_models is well-suited to low-latency chat and routing, request routing and triage, text classification.
How do I use nemo_baseline_models in osFoundry?
Paste your chime-dasr API key in the key dialog (or deploy the open weights for self-hostable models), assign nemo_baseline_models to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by chime-dasr on February 15, 2024. Source: https://huggingface.co/chime-dasr/nemo_baseline_models