wh_med_mucs_30_70_flattened_mucs_52553__val_finetune_trial
Built by dianavdavidson, wh_med_mucs_30_70_flattened_mucs_52553__val_finetune_trial is an speech-and-audio model. wh_med_mucs_30_70_flattened_mucs_52553__val_finetune_trial is an open-weights audio model.
by dianavdavidson
Best for
- automatic speech recognition
Ways to use wh_med_mucs_30_70_flattened_mucs_52553__val_finetune_trial in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your dianavdavidson API key. osFoundry discovers wh_med_mucs_30_70_flattened_mucs_52553__val_finetune_trial 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
wh_med_mucs_30_70_flattened_mucs_52553__val_finetune_trial 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.
wh_med_mucs_30_70_flattened_mucs_52553__val_finetune_trial vs similar models
| Model | Org | Params | Context | Input price | Self-host |
|---|
| wh_med_mucs_30_70_flattened_mucs_52553__val_finetune_trial | dianavdavidson | — | — | Free (local) | Yes |
| qwen3-asr-uzbek-v2 | Gearnode | — | — | Free (local) | Yes |
| mms-300m-mlg-onitsikix | waxal-benchmarking | — | — | Free (local) | Yes |
| garchen-stt | billingsmoore | — | — | Free (local) | Yes |
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about wh_med_mucs_30_70_flattened_mucs_52553__val_finetune_trial
Is wh_med_mucs_30_70_flattened_mucs_52553__val_finetune_trial free to use?
wh_med_mucs_30_70_flattened_mucs_52553__val_finetune_trial 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 wh_med_mucs_30_70_flattened_mucs_52553__val_finetune_trial 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 wh_med_mucs_30_70_flattened_mucs_52553__val_finetune_trial locally?
Yes. wh_med_mucs_30_70_flattened_mucs_52553__val_finetune_trial is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is wh_med_mucs_30_70_flattened_mucs_52553__val_finetune_trial best at?
wh_med_mucs_30_70_flattened_mucs_52553__val_finetune_trial is well-suited to automatic speech recognition.
How do I use wh_med_mucs_30_70_flattened_mucs_52553__val_finetune_trial in osFoundry?
Paste your dianavdavidson API key in the key dialog (or deploy the open weights for self-hostable models), assign wh_med_mucs_30_70_flattened_mucs_52553__val_finetune_trial to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by dianavdavidson on April 17, 2026. Source: https://huggingface.co/dianavdavidson/wh_med_mucs_30_70_flattened_mucs_52553__val_finetune_trial