Vedika_coder
Vedika_coder (Vedika35, 2026) is an chat model. Vedika_coder is an open-weights chat model.
by Vedika35
Best for
Ways to use Vedika_coder in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your Vedika35 API key. osFoundry discovers Vedika_coder 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
Vedika_coder 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.
Vedika_coder vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Vedika_coder
Is Vedika_coder free to use?
Vedika_coder 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 Vedika_coder 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 Vedika_coder locally?
Yes. Vedika_coder is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Vedika_coder best at?
Vedika_coder is well-suited to text generation.
How do I use Vedika_coder in osFoundry?
Paste your Vedika35 API key in the key dialog (or deploy the open weights for self-hostable models), assign Vedika_coder to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by Vedika35 on April 26, 2026. Source: https://huggingface.co/Vedika35/Vedika_coder