tiny-Qwen2_5_VLForConditionalGeneration
tiny-Qwen2_5_VLForConditionalGeneration is a image-generation model from trl-internal-testing, released July 20, 2025. tiny-Qwen2_5_VLForConditionalGeneration is an open-weights image model.
by trl-internal-testing
Best for
Ways to use tiny-Qwen2_5_VLForConditionalGeneration in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your trl-internal-testing API key. osFoundry discovers tiny-Qwen2_5_VLForConditionalGeneration 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
tiny-Qwen2_5_VLForConditionalGeneration 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.
tiny-Qwen2_5_VLForConditionalGeneration vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about tiny-Qwen2_5_VLForConditionalGeneration
Is tiny-Qwen2_5_VLForConditionalGeneration free to use?
tiny-Qwen2_5_VLForConditionalGeneration 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 tiny-Qwen2_5_VLForConditionalGeneration 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 tiny-Qwen2_5_VLForConditionalGeneration locally?
Yes. tiny-Qwen2_5_VLForConditionalGeneration is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is tiny-Qwen2_5_VLForConditionalGeneration best at?
tiny-Qwen2_5_VLForConditionalGeneration is well-suited to image text to text.
How do I use tiny-Qwen2_5_VLForConditionalGeneration in osFoundry?
Paste your trl-internal-testing API key in the key dialog (or deploy the open weights for self-hostable models), assign tiny-Qwen2_5_VLForConditionalGeneration to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by trl-internal-testing on July 20, 2025. Source: https://huggingface.co/trl-internal-testing/tiny-Qwen2_5_VLForConditionalGeneration