Smaug-Llama-3-70B-Instruct-32K
Smaug-Llama-3-70B-Instruct-32K (abacusai, 2024) is a 70 billion parameter chat model. Smaug-Llama-3-70B-Instruct-32K is an open-weights chat model with roughly 70 billion parameters.
by abacusai · 70B parameters
Best for
Ways to use Smaug-Llama-3-70B-Instruct-32K in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your abacusai API key. osFoundry discovers Smaug-Llama-3-70B-Instruct-32K 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
Smaug-Llama-3-70B-Instruct-32K 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 Smaug-Llama-3-70B-Instruct-32K
Smaug-Llama-3-70B-Instruct-32K runs on a single A100 80GB or H100 80GB at Q4 quantisation (~42 GB VRAM with KV-cache headroom). Full-precision inference requires multiple H100/H200 GPUs at FP16 (~168 GB).
Smaug-Llama-3-70B-Instruct-32K vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Smaug-Llama-3-70B-Instruct-32K
Is Smaug-Llama-3-70B-Instruct-32K free to use?
Smaug-Llama-3-70B-Instruct-32K 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 Smaug-Llama-3-70B-Instruct-32K 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 Smaug-Llama-3-70B-Instruct-32K need?
Approximately 42 GB at Q4 quantisation, or 168 GB at full FP16 precision. Fits on a single A100/H100 80GB.
Can I run Smaug-Llama-3-70B-Instruct-32K locally?
Yes. Smaug-Llama-3-70B-Instruct-32K is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Smaug-Llama-3-70B-Instruct-32K best at?
Smaug-Llama-3-70B-Instruct-32K is well-suited to text generation.
How do I use Smaug-Llama-3-70B-Instruct-32K in osFoundry?
Paste your abacusai API key in the key dialog (or deploy the open weights for self-hostable models), assign Smaug-Llama-3-70B-Instruct-32K to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by abacusai on June 11, 2024. Source: https://huggingface.co/abacusai/Smaug-Llama-3-70B-Instruct-32K