beitv2_large_patch16_224.in1k_ft_in22k
timm's beitv2_large_patch16_224.in1k_ft_in22k is a image-generation model. beitv2_large_patch16_224.in1k_ft_in22k is an open-weights image model.
by timm
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Ways to use beitv2_large_patch16_224.in1k_ft_in22k in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your timm API key. osFoundry discovers beitv2_large_patch16_224.in1k_ft_in22k 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
beitv2_large_patch16_224.in1k_ft_in22k 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.
beitv2_large_patch16_224.in1k_ft_in22k vs similar models
| Model | Org | Params | Context | Input price | Self-host |
|---|
| beitv2_large_patch16_224.in1k_ft_in22k | timm | — | — | Free (local) | Yes |
| LTX-2.3_Gemma | lightweight | — | — | Free (local) | Yes |
| test | shinonome4649ne | — | — | Free (local) | Yes |
| A.X-4.0-VL-Light | skt | — | — | Free (local) | Yes |
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about beitv2_large_patch16_224.in1k_ft_in22k
Is beitv2_large_patch16_224.in1k_ft_in22k free to use?
beitv2_large_patch16_224.in1k_ft_in22k 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 beitv2_large_patch16_224.in1k_ft_in22k 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 beitv2_large_patch16_224.in1k_ft_in22k locally?
Yes. beitv2_large_patch16_224.in1k_ft_in22k is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is beitv2_large_patch16_224.in1k_ft_in22k best at?
beitv2_large_patch16_224.in1k_ft_in22k is well-suited to image classification.
How do I use beitv2_large_patch16_224.in1k_ft_in22k in osFoundry?
Paste your timm API key in the key dialog (or deploy the open weights for self-hostable models), assign beitv2_large_patch16_224.in1k_ft_in22k to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by timm on December 23, 2022. Source: https://huggingface.co/timm/beitv2_large_patch16_224.in1k_ft_in22k