embeddinggemma-300m-qat-q4_0-unquantized
Built by unsloth, embeddinggemma-300m-qat-q4_0-unquantized is an embedding model. embeddinggemma-300m-qat-q4_0-unquantized is an open-weights embed model.
by unsloth
Best for
Ways to use embeddinggemma-300m-qat-q4_0-unquantized in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your unsloth API key. osFoundry discovers embeddinggemma-300m-qat-q4_0-unquantized 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
embeddinggemma-300m-qat-q4_0-unquantized 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.
embeddinggemma-300m-qat-q4_0-unquantized vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about embeddinggemma-300m-qat-q4_0-unquantized
Is embeddinggemma-300m-qat-q4_0-unquantized free to use?
embeddinggemma-300m-qat-q4_0-unquantized 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 embeddinggemma-300m-qat-q4_0-unquantized 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 embeddinggemma-300m-qat-q4_0-unquantized locally?
Yes. embeddinggemma-300m-qat-q4_0-unquantized is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is embeddinggemma-300m-qat-q4_0-unquantized best at?
embeddinggemma-300m-qat-q4_0-unquantized is well-suited to sentence similarity.
How do I use embeddinggemma-300m-qat-q4_0-unquantized in osFoundry?
Paste your unsloth API key in the key dialog (or deploy the open weights for self-hostable models), assign embeddinggemma-300m-qat-q4_0-unquantized to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by unsloth on September 4, 2025. Source: https://huggingface.co/unsloth/embeddinggemma-300m-qat-q4_0-unquantized