I-DLM-8B-lora-r128
yifanyu's I-DLM-8B-lora-r128 packs 8 billion parameters into a chat model. I-DLM-8B-lora-r128 is an open-weights chat model with roughly 8 billion parameters.
by yifanyu · 8B parameters
Best for
Ways to use I-DLM-8B-lora-r128 in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your yifanyu API key. osFoundry discovers I-DLM-8B-lora-r128 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
I-DLM-8B-lora-r128 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 I-DLM-8B-lora-r128
I-DLM-8B-lora-r128 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).
I-DLM-8B-lora-r128 vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about I-DLM-8B-lora-r128
Is I-DLM-8B-lora-r128 free to use?
I-DLM-8B-lora-r128 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 I-DLM-8B-lora-r128 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 I-DLM-8B-lora-r128 need?
Approximately 5 GB at Q4 quantisation, or 20 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run I-DLM-8B-lora-r128 locally?
Yes. I-DLM-8B-lora-r128 is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is I-DLM-8B-lora-r128 best at?
I-DLM-8B-lora-r128 is well-suited to text generation.
How do I use I-DLM-8B-lora-r128 in osFoundry?
Paste your yifanyu API key in the key dialog (or deploy the open weights for self-hostable models), assign I-DLM-8B-lora-r128 to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by yifanyu on April 7, 2026. Source: https://huggingface.co/yifanyu/I-DLM-8B-lora-r128