Lorenzo-8B-Merge
Lorenzo-8B-Merge is a 8 billion parameter chat model from qingy2024, released November 22, 2024. Lorenzo-8B-Merge is an open-weights chat model with roughly 8 billion parameters.
by qingy2024 · 8B parameters
Best for
Ways to use Lorenzo-8B-Merge in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your qingy2024 API key. osFoundry discovers Lorenzo-8B-Merge 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
Lorenzo-8B-Merge 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 Lorenzo-8B-Merge
Lorenzo-8B-Merge runs on a single 16GB consumer GPU (~5 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~20 GB).
Lorenzo-8B-Merge vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Lorenzo-8B-Merge
Is Lorenzo-8B-Merge free to use?
Lorenzo-8B-Merge 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 Lorenzo-8B-Merge 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 Lorenzo-8B-Merge need?
Approximately 5 GB at Q4 quantisation, or 20 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Lorenzo-8B-Merge locally?
Yes. Lorenzo-8B-Merge is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Lorenzo-8B-Merge best at?
Lorenzo-8B-Merge is well-suited to text generation.
How do I use Lorenzo-8B-Merge in osFoundry?
Paste your qingy2024 API key in the key dialog (or deploy the open weights for self-hostable models), assign Lorenzo-8B-Merge to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by qingy2024 on November 22, 2024. Source: https://huggingface.co/qingy2024/Lorenzo-8B-Merge