meme-namer-floodgate-Qwen36-27B-lora
atefarabi's meme-namer-floodgate-Qwen36-27B-lora packs 27 billion parameters into a image-generation model. meme-namer-floodgate-Qwen36-27B-lora is an open-weights image model with roughly 27 billion parameters.
by atefarabi · 27B parameters
Best for
Ways to use meme-namer-floodgate-Qwen36-27B-lora in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your atefarabi API key. osFoundry discovers meme-namer-floodgate-Qwen36-27B-lora 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
meme-namer-floodgate-Qwen36-27B-lora 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 meme-namer-floodgate-Qwen36-27B-lora
meme-namer-floodgate-Qwen36-27B-lora runs on a 24GB consumer or workstation GPU (~17 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~65 GB).
meme-namer-floodgate-Qwen36-27B-lora vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about meme-namer-floodgate-Qwen36-27B-lora
Is meme-namer-floodgate-Qwen36-27B-lora free to use?
meme-namer-floodgate-Qwen36-27B-lora 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 meme-namer-floodgate-Qwen36-27B-lora 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 meme-namer-floodgate-Qwen36-27B-lora need?
Approximately 17 GB at Q4 quantisation, or 65 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run meme-namer-floodgate-Qwen36-27B-lora locally?
Yes. meme-namer-floodgate-Qwen36-27B-lora is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is meme-namer-floodgate-Qwen36-27B-lora best at?
meme-namer-floodgate-Qwen36-27B-lora is well-suited to image text to text.
How do I use meme-namer-floodgate-Qwen36-27B-lora in osFoundry?
Paste your atefarabi API key in the key dialog (or deploy the open weights for self-hostable models), assign meme-namer-floodgate-Qwen36-27B-lora to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by atefarabi on April 24, 2026. Source: https://huggingface.co/atefarabi/meme-namer-floodgate-Qwen36-27B-lora