BlueLM-7B-Chat-32K
vivo-ai's BlueLM-7B-Chat-32K packs 7 billion parameters into a chat model. BlueLM-7B-Chat-32K is an open-weights chat model with roughly 7 billion parameters.
by vivo-ai · 7B parameters
Best for
Ways to use BlueLM-7B-Chat-32K in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your vivo-ai API key. osFoundry discovers BlueLM-7B-Chat-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
BlueLM-7B-Chat-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 BlueLM-7B-Chat-32K
BlueLM-7B-Chat-32K 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 (~17 GB).
BlueLM-7B-Chat-32K vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about BlueLM-7B-Chat-32K
Is BlueLM-7B-Chat-32K free to use?
BlueLM-7B-Chat-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 BlueLM-7B-Chat-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 BlueLM-7B-Chat-32K need?
Approximately 5 GB at Q4 quantisation, or 17 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run BlueLM-7B-Chat-32K locally?
Yes. BlueLM-7B-Chat-32K is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is BlueLM-7B-Chat-32K best at?
BlueLM-7B-Chat-32K is well-suited to text generation.
How do I use BlueLM-7B-Chat-32K in osFoundry?
Paste your vivo-ai API key in the key dialog (or deploy the open weights for self-hostable models), assign BlueLM-7B-Chat-32K to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by vivo-ai on October 17, 2023. Source: https://huggingface.co/vivo-ai/BlueLM-7B-Chat-32K