Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform
Released by nm-testing in 2024, Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform is a 70 billion parameter chat model. Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform is an open-weights chat model with roughly 70 billion parameters.
by nm-testing · 70B parameters
Best for
Ways to use Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your nm-testing API key. osFoundry discovers Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform 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
Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform 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 Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform
Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform 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).
Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform
Is Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform free to use?
Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform 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 Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform 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 Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform need?
Approximately 42 GB at Q4 quantisation, or 168 GB at full FP16 precision. Fits on a single A100/H100 80GB.
Can I run Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform locally?
Yes. Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform best at?
Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform is well-suited to text generation.
How do I use Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform in osFoundry?
Paste your nm-testing API key in the key dialog (or deploy the open weights for self-hostable models), assign Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by nm-testing on July 20, 2024. Source: https://huggingface.co/nm-testing/Meta-Llama-3-70B-Instruct-FBGEMM-nonuniform