Qwen2.5-0.5B-Instruct-Gensyn-Swarm-twitchy_pale_hummingbird
Yurg99's Qwen2.5-0.5B-Instruct-Gensyn-Swarm-twitchy_pale_hummingbird packs 1 billion parameters into a chat model. Qwen2.5-0.5B-Instruct-Gensyn-Swarm-twitchy_pale_hummingbird is an open-weights chat model with roughly 1 billion parameters.
by Yurg99 · 1B parameters
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Ways to use Qwen2.5-0.5B-Instruct-Gensyn-Swarm-twitchy_pale_hummingbird in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your Yurg99 API key. osFoundry discovers Qwen2.5-0.5B-Instruct-Gensyn-Swarm-twitchy_pale_hummingbird 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
Qwen2.5-0.5B-Instruct-Gensyn-Swarm-twitchy_pale_hummingbird 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.
What hardware can run Qwen2.5-0.5B-Instruct-Gensyn-Swarm-twitchy_pale_hummingbird
Qwen2.5-0.5B-Instruct-Gensyn-Swarm-twitchy_pale_hummingbird runs on a single 16GB consumer GPU (~1 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~3 GB).
Qwen2.5-0.5B-Instruct-Gensyn-Swarm-twitchy_pale_hummingbird vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Qwen2.5-0.5B-Instruct-Gensyn-Swarm-twitchy_pale_hummingbird
Is Qwen2.5-0.5B-Instruct-Gensyn-Swarm-twitchy_pale_hummingbird free to use?
Qwen2.5-0.5B-Instruct-Gensyn-Swarm-twitchy_pale_hummingbird 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 Qwen2.5-0.5B-Instruct-Gensyn-Swarm-twitchy_pale_hummingbird commercially?
Commercial use is allowed with conditions. Licence terms not specified — verify the upstream model card before commercial use. Check upstream documentation.
How much VRAM does Qwen2.5-0.5B-Instruct-Gensyn-Swarm-twitchy_pale_hummingbird need?
Approximately 1 GB at Q4 quantisation, or 3 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Qwen2.5-0.5B-Instruct-Gensyn-Swarm-twitchy_pale_hummingbird locally?
Yes. Qwen2.5-0.5B-Instruct-Gensyn-Swarm-twitchy_pale_hummingbird is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Qwen2.5-0.5B-Instruct-Gensyn-Swarm-twitchy_pale_hummingbird best at?
Qwen2.5-0.5B-Instruct-Gensyn-Swarm-twitchy_pale_hummingbird is well-suited to text generation.
How do I use Qwen2.5-0.5B-Instruct-Gensyn-Swarm-twitchy_pale_hummingbird in osFoundry?
Paste your Yurg99 API key in the key dialog (or deploy the open weights for self-hostable models), assign Qwen2.5-0.5B-Instruct-Gensyn-Swarm-twitchy_pale_hummingbird to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by Yurg99 on November 2, 2025. Source: https://huggingface.co/Yurg99/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-twitchy_pale_hummingbird