CHAI_SFT_model_8b
Built by chancharikm, CHAI_SFT_model_8b is a 8 billion parameter video-generation model. CHAI_SFT_model_8b is an open-weights video model with roughly 8 billion parameters.
by chancharikm · 8B parameters
Best for
Ways to use CHAI_SFT_model_8b in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your chancharikm API key. osFoundry discovers CHAI_SFT_model_8b 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
CHAI_SFT_model_8b 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 CHAI_SFT_model_8b
CHAI_SFT_model_8b 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 (~20 GB).
CHAI_SFT_model_8b vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about CHAI_SFT_model_8b
Is CHAI_SFT_model_8b free to use?
CHAI_SFT_model_8b 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 CHAI_SFT_model_8b 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 CHAI_SFT_model_8b need?
Approximately 5 GB at Q4 quantisation, or 20 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run CHAI_SFT_model_8b locally?
Yes. CHAI_SFT_model_8b is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is CHAI_SFT_model_8b best at?
CHAI_SFT_model_8b is well-suited to video text to text.
How do I use CHAI_SFT_model_8b in osFoundry?
Paste your chancharikm API key in the key dialog (or deploy the open weights for self-hostable models), assign CHAI_SFT_model_8b to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by chancharikm on November 26, 2025. Source: https://huggingface.co/chancharikm/CHAI_SFT_model_8b