ResNeXt50
ResNeXt50 (qualcomm, 2024) is an image-generation model. ResNeXt50 is an open-weights image model.
by qualcomm
Best for
Ways to use ResNeXt50 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your qualcomm API key. osFoundry discovers ResNeXt50 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
ResNeXt50 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.
ResNeXt50 vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about ResNeXt50
Is ResNeXt50 free to use?
ResNeXt50 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 ResNeXt50 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 ResNeXt50 locally?
Yes. ResNeXt50 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is ResNeXt50 best at?
ResNeXt50 is well-suited to image classification.
How do I use ResNeXt50 in osFoundry?
Paste your qualcomm API key in the key dialog (or deploy the open weights for self-hostable models), assign ResNeXt50 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by qualcomm on February 25, 2024. Source: https://huggingface.co/qualcomm/ResNeXt50