camembert-base-wikipedia-4gb
almanach's camembert-base-wikipedia-4gb is a chat model. camembert-base-wikipedia-4gb is an open-weights chat model.
by almanach
Best for
- low-latency chat and routing
- request routing and triage
- text classification
Ways to use camembert-base-wikipedia-4gb in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your almanach API key. osFoundry discovers camembert-base-wikipedia-4gb 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
camembert-base-wikipedia-4gb 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.
camembert-base-wikipedia-4gb vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about camembert-base-wikipedia-4gb
Is camembert-base-wikipedia-4gb free to use?
camembert-base-wikipedia-4gb 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 camembert-base-wikipedia-4gb commercially?
Commercial use is allowed with conditions. Licence terms not specified — verify the upstream model card before commercial use. Check upstream documentation.
Can I run camembert-base-wikipedia-4gb locally?
Yes. camembert-base-wikipedia-4gb is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is camembert-base-wikipedia-4gb best at?
camembert-base-wikipedia-4gb is well-suited to low-latency chat and routing, request routing and triage, text classification.
How do I use camembert-base-wikipedia-4gb in osFoundry?
Paste your almanach API key in the key dialog (or deploy the open weights for self-hostable models), assign camembert-base-wikipedia-4gb to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by almanach on March 2, 2022. Source: https://huggingface.co/almanach/camembert-base-wikipedia-4gb