eaea7be-bert_qnli_ClassDetection
quanda-bench-test's eaea7be-bert_qnli_ClassDetection is a chat model. eaea7be-bert_qnli_ClassDetection is an open-weights chat model.
by quanda-bench-test
Best for
- low-latency chat and routing
- request routing and triage
- text classification
Ways to use eaea7be-bert_qnli_ClassDetection in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your quanda-bench-test API key. osFoundry discovers eaea7be-bert_qnli_ClassDetection 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
eaea7be-bert_qnli_ClassDetection 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.
eaea7be-bert_qnli_ClassDetection vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about eaea7be-bert_qnli_ClassDetection
Is eaea7be-bert_qnli_ClassDetection free to use?
eaea7be-bert_qnli_ClassDetection 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 eaea7be-bert_qnli_ClassDetection 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 eaea7be-bert_qnli_ClassDetection locally?
Yes. eaea7be-bert_qnli_ClassDetection is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is eaea7be-bert_qnli_ClassDetection best at?
eaea7be-bert_qnli_ClassDetection is well-suited to low-latency chat and routing, request routing and triage, text classification.
How do I use eaea7be-bert_qnli_ClassDetection in osFoundry?
Paste your quanda-bench-test API key in the key dialog (or deploy the open weights for self-hostable models), assign eaea7be-bert_qnli_ClassDetection to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by quanda-bench-test on April 15, 2026. Source: https://huggingface.co/quanda-bench-test/eaea7be-bert_qnli_ClassDetection