wem_sentiment_model_ollama
tgama's wem_sentiment_model_ollama is a chat model. wem_sentiment_model_ollama is an open-weights chat model.
by tgama
Best for
- low-latency chat and routing
- request routing and triage
- text classification
Ways to use wem_sentiment_model_ollama in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your tgama API key. osFoundry discovers wem_sentiment_model_ollama 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
wem_sentiment_model_ollama 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.
wem_sentiment_model_ollama vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about wem_sentiment_model_ollama
Is wem_sentiment_model_ollama free to use?
wem_sentiment_model_ollama 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 wem_sentiment_model_ollama 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 wem_sentiment_model_ollama locally?
Yes. wem_sentiment_model_ollama is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is wem_sentiment_model_ollama best at?
wem_sentiment_model_ollama is well-suited to low-latency chat and routing, request routing and triage, text classification.
How do I use wem_sentiment_model_ollama in osFoundry?
Paste your tgama API key in the key dialog (or deploy the open weights for self-hostable models), assign wem_sentiment_model_ollama to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by tgama on June 15, 2024. Source: https://huggingface.co/tgama/wem_sentiment_model_ollama