Mini-InternVL2-1B-DA-Medical
OpenGVLab's Mini-InternVL2-1B-DA-Medical packs 1 billion parameters into a image-generation model. Mini-InternVL2-1B-DA-Medical is an open-weights image model with roughly 1 billion parameters.
by OpenGVLab · 1B parameters
Best for
Ways to use Mini-InternVL2-1B-DA-Medical in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your OpenGVLab API key. osFoundry discovers Mini-InternVL2-1B-DA-Medical 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
Mini-InternVL2-1B-DA-Medical 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 Mini-InternVL2-1B-DA-Medical
Mini-InternVL2-1B-DA-Medical runs on a single 16GB consumer GPU (~1 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~3 GB).
Mini-InternVL2-1B-DA-Medical vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Mini-InternVL2-1B-DA-Medical
Is Mini-InternVL2-1B-DA-Medical free to use?
Mini-InternVL2-1B-DA-Medical 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 Mini-InternVL2-1B-DA-Medical 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 Mini-InternVL2-1B-DA-Medical need?
Approximately 1 GB at Q4 quantisation, or 3 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Mini-InternVL2-1B-DA-Medical locally?
Yes. Mini-InternVL2-1B-DA-Medical is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Mini-InternVL2-1B-DA-Medical best at?
Mini-InternVL2-1B-DA-Medical is well-suited to image text to text.
How do I use Mini-InternVL2-1B-DA-Medical in osFoundry?
Paste your OpenGVLab API key in the key dialog (or deploy the open weights for self-hostable models), assign Mini-InternVL2-1B-DA-Medical to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by OpenGVLab on December 7, 2024. Source: https://huggingface.co/OpenGVLab/Mini-InternVL2-1B-DA-Medical