fare4-clip
fare4-clip (chs20, 2024) is an image-generation model. fare4-clip is an open-weights image model.
by chs20
Best for
- zero shot image classification
Ways to use fare4-clip in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your chs20 API key. osFoundry discovers fare4-clip 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
fare4-clip 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.
fare4-clip vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about fare4-clip
Is fare4-clip free to use?
fare4-clip 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 fare4-clip 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 fare4-clip locally?
Yes. fare4-clip is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is fare4-clip best at?
fare4-clip is well-suited to zero shot image classification.
How do I use fare4-clip in osFoundry?
Paste your chs20 API key in the key dialog (or deploy the open weights for self-hostable models), assign fare4-clip to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by chs20 on February 23, 2024. Source: https://huggingface.co/chs20/fare4-clip