ternary-weight-embedding
Released by malenia1 in 2024, ternary-weight-embedding is an chat model. ternary-weight-embedding is an open-weights chat model.
by malenia1
Best for
- low-latency chat and routing
- request routing and triage
- text classification
Ways to use ternary-weight-embedding in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your malenia1 API key. osFoundry discovers ternary-weight-embedding 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
ternary-weight-embedding 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.
ternary-weight-embedding vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about ternary-weight-embedding
Is ternary-weight-embedding free to use?
ternary-weight-embedding 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 ternary-weight-embedding 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 ternary-weight-embedding locally?
Yes. ternary-weight-embedding is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is ternary-weight-embedding best at?
ternary-weight-embedding is well-suited to low-latency chat and routing, request routing and triage, text classification.
How do I use ternary-weight-embedding in osFoundry?
Paste your malenia1 API key in the key dialog (or deploy the open weights for self-hostable models), assign ternary-weight-embedding to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by malenia1 on October 23, 2024. Source: https://huggingface.co/malenia1/ternary-weight-embedding