Ollama_Quantised_LLaVA-NeXT-Video-7B-DPO
Ollama_Quantised_LLaVA-NeXT-Video-7B-DPO is a 7 billion parameter embedding model from ManishThota, released June 29, 2024. Ollama_Quantised_LLaVA-NeXT-Video-7B-DPO is an open-weights embed model with roughly 7 billion parameters.
by ManishThota · 7B parameters
Best for
Ways to use Ollama_Quantised_LLaVA-NeXT-Video-7B-DPO in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your ManishThota API key. osFoundry discovers Ollama_Quantised_LLaVA-NeXT-Video-7B-DPO 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
Ollama_Quantised_LLaVA-NeXT-Video-7B-DPO 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.
What hardware can run Ollama_Quantised_LLaVA-NeXT-Video-7B-DPO
Ollama_Quantised_LLaVA-NeXT-Video-7B-DPO runs on a single 16GB consumer GPU (~5 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~17 GB).
Ollama_Quantised_LLaVA-NeXT-Video-7B-DPO vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Ollama_Quantised_LLaVA-NeXT-Video-7B-DPO
Is Ollama_Quantised_LLaVA-NeXT-Video-7B-DPO free to use?
Ollama_Quantised_LLaVA-NeXT-Video-7B-DPO 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 Ollama_Quantised_LLaVA-NeXT-Video-7B-DPO commercially?
Commercial use is allowed with conditions. Licence terms not specified — verify the upstream model card before commercial use. Check upstream documentation.
How much VRAM does Ollama_Quantised_LLaVA-NeXT-Video-7B-DPO need?
Approximately 5 GB at Q4 quantisation, or 17 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Ollama_Quantised_LLaVA-NeXT-Video-7B-DPO locally?
Yes. Ollama_Quantised_LLaVA-NeXT-Video-7B-DPO is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Ollama_Quantised_LLaVA-NeXT-Video-7B-DPO best at?
Ollama_Quantised_LLaVA-NeXT-Video-7B-DPO is well-suited to feature extraction.
How do I use Ollama_Quantised_LLaVA-NeXT-Video-7B-DPO in osFoundry?
Paste your ManishThota API key in the key dialog (or deploy the open weights for self-hostable models), assign Ollama_Quantised_LLaVA-NeXT-Video-7B-DPO to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by ManishThota on June 29, 2024. Source: https://huggingface.co/ManishThota/Ollama_Quantised_LLaVA-NeXT-Video-7B-DPO