csmpt-7B-RAGsum
Released by BUT-FIT in 2024, csmpt-7B-RAGsum is a 7 billion parameter chat model. csmpt-7B-RAGsum is an open-weights chat model with roughly 7 billion parameters.
by BUT-FIT · 7B parameters
Best for
Ways to use csmpt-7B-RAGsum in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your BUT-FIT API key. osFoundry discovers csmpt-7B-RAGsum 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
csmpt-7B-RAGsum 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 csmpt-7B-RAGsum
csmpt-7B-RAGsum 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).
csmpt-7B-RAGsum vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about csmpt-7B-RAGsum
Is csmpt-7B-RAGsum free to use?
csmpt-7B-RAGsum 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 csmpt-7B-RAGsum 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 csmpt-7B-RAGsum need?
Approximately 5 GB at Q4 quantisation, or 17 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run csmpt-7B-RAGsum locally?
Yes. csmpt-7B-RAGsum is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is csmpt-7B-RAGsum best at?
csmpt-7B-RAGsum is well-suited to text generation.
How do I use csmpt-7B-RAGsum in osFoundry?
Paste your BUT-FIT API key in the key dialog (or deploy the open weights for self-hostable models), assign csmpt-7B-RAGsum to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by BUT-FIT on December 9, 2024. Source: https://huggingface.co/BUT-FIT/csmpt-7B-RAGsum