army_model_gemma2b
Built by chunye97, army_model_gemma2b is a 2 billion parameter chat model. army_model_gemma2b is an open-weights chat model with roughly 2 billion parameters.
by chunye97 · 2B parameters
Best for
Ways to use army_model_gemma2b in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your chunye97 API key. osFoundry discovers army_model_gemma2b 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
army_model_gemma2b 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 army_model_gemma2b
army_model_gemma2b runs on a single 16GB consumer GPU (~2 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~5 GB).
army_model_gemma2b vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about army_model_gemma2b
Is army_model_gemma2b free to use?
army_model_gemma2b 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 army_model_gemma2b 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 army_model_gemma2b need?
Approximately 2 GB at Q4 quantisation, or 5 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run army_model_gemma2b locally?
Yes. army_model_gemma2b is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is army_model_gemma2b best at?
army_model_gemma2b is well-suited to text generation.
How do I use army_model_gemma2b in osFoundry?
Paste your chunye97 API key in the key dialog (or deploy the open weights for self-hostable models), assign army_model_gemma2b to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by chunye97 on April 15, 2026. Source: https://huggingface.co/chunye97/army_model_gemma2b