MLX_google_gemma-2b-it_testing
MLX_google_gemma-2b-it_testing is a 2 billion parameter chat model from uirev, released June 12, 2024. MLX_google_gemma-2b-it_testing is an open-weights chat model with roughly 2 billion parameters.
by uirev · 2B parameters
Best for
Ways to use MLX_google_gemma-2b-it_testing in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your uirev API key. osFoundry discovers MLX_google_gemma-2b-it_testing 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
MLX_google_gemma-2b-it_testing 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 MLX_google_gemma-2b-it_testing
MLX_google_gemma-2b-it_testing 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).
MLX_google_gemma-2b-it_testing vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about MLX_google_gemma-2b-it_testing
Is MLX_google_gemma-2b-it_testing free to use?
MLX_google_gemma-2b-it_testing 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 MLX_google_gemma-2b-it_testing 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 MLX_google_gemma-2b-it_testing need?
Approximately 2 GB at Q4 quantisation, or 5 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run MLX_google_gemma-2b-it_testing locally?
Yes. MLX_google_gemma-2b-it_testing is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is MLX_google_gemma-2b-it_testing best at?
MLX_google_gemma-2b-it_testing is well-suited to text generation.
How do I use MLX_google_gemma-2b-it_testing in osFoundry?
Paste your uirev API key in the key dialog (or deploy the open weights for self-hostable models), assign MLX_google_gemma-2b-it_testing to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by uirev on June 12, 2024. Source: https://huggingface.co/uirev/MLX_google_gemma-2b-it_testing