Tess-2.0-Llama-3-8B
migtissera's Tess-2.0-Llama-3-8B packs 8 billion parameters into a chat model. Tess-2.0-Llama-3-8B is an open-weights chat model with roughly 8 billion parameters.
by migtissera · 8B parameters
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Ways to use Tess-2.0-Llama-3-8B in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your migtissera API key. osFoundry discovers Tess-2.0-Llama-3-8B 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
Tess-2.0-Llama-3-8B 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 Tess-2.0-Llama-3-8B
Tess-2.0-Llama-3-8B 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).
Tess-2.0-Llama-3-8B vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Tess-2.0-Llama-3-8B
Is Tess-2.0-Llama-3-8B free to use?
Tess-2.0-Llama-3-8B 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 Tess-2.0-Llama-3-8B 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 Tess-2.0-Llama-3-8B need?
Approximately 5 GB at Q4 quantisation, or 20 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Tess-2.0-Llama-3-8B locally?
Yes. Tess-2.0-Llama-3-8B is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Tess-2.0-Llama-3-8B best at?
Tess-2.0-Llama-3-8B is well-suited to text generation.
How do I use Tess-2.0-Llama-3-8B in osFoundry?
Paste your migtissera API key in the key dialog (or deploy the open weights for self-hostable models), assign Tess-2.0-Llama-3-8B to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by migtissera on May 5, 2024. Source: https://huggingface.co/migtissera/Tess-2.0-Llama-3-8B