8bcustom-model is an 8B-class local coding assistant model/runtime release built for Korean developers who need practical help with Linux, Docker, vLLM, Open-WebUI, CUDA, JSONL datasets, and LoRA workflows.

This repository is part of a DGX AI Factory-style local LLM deployment project: data preparation, LoRA repair, model merge, vLLM serving, Open-WebUI integration, systemd autostart, benchmarking, and Hugging Face release packaging.

What this model is for

This model is designed as a practical development assistant for:

Linux command troubleshooting
Docker and service deployment
vLLM OpenAI-compatible serving
Open-WebUI connection setup
CUDA/PyTorch environment checks
JSONL dataset validation
LoRA training and repair workflows
Korean step-by-step developer support

The target behavior is direct, procedural, and operational: diagnose the problem, provide exact commands, and explain the result clearly in Korean honorific style.

Validated local runtime

The model was validated in a local production-style runtime:

Component	Status
vLLM OpenAI-compatible API	Working
Open-WebUI integration	Working
systemd autostart	Working
Local model name	`dgx-stable-current`
Public release name	`8bcustom-model`
Hugging Face public repo	`koreallmdev/8bcustom-model`

Benchmark summary

The final deployment benchmark used a router/template runtime hardening layer for operational reliability.

Metric	Result
Average score	97.75
Pass ≥ 70	20 / 20
Strong ≥ 85	20 / 20
Critical failures	0
Decision	DEPLOY_CANDIDATE

The benchmark focused on practical developer operations such as Linux, Docker, CUDA checks, vLLM serving, JSONL validation, FastAPI, systemd troubleshooting, LoRA policy, and Korean response quality.

Runtime policy

For production usage, the local deployment uses a hybrid approach:

General coding questions: model generation
Linux/vLLM/CUDA/systemd known operational routes: guarded templates
LoRA/stable/rejected model policy: fixed policy templates
CJK leakage and style regressions: post-check and route hardening

This approach keeps the model useful for open-ended coding while making high-risk operational answers more deterministic.

Quick start with vLLM

After downloading the model files, you can serve the model with vLLM:

bash

python -m vllm.entrypoints.openai.api_server \
  --model ./ \
  --served-model-name 8bcustom-model \
  --dtype float16 \
  --host 0.0.0.0 \
  --port 8000 \
  --max-model-len 1536 \
  --gpu-memory-utilization 0.50 \
  --max-num-seqs 8

Check the model endpoint:

curl http://127.0.0.1:8000/v1/models

Send a test request:

bash

curl http://127.0.0.1:8000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "8bcustom-model",
    "messages": [
      {
        "role": "user",
        "content": "Docker 컨테이너가 실행 중인지 확인하는 명령어를 알려주세요."
      }
    ],
    "temperature": 0.2,
    "max_tokens": 300
  }'

Open-WebUI connection

For Open-WebUI, add an OpenAI-compatible API connection.

If Open-WebUI runs in Docker:

text

Base URL: http://host.docker.internal:8000/v1
API Key : dummy
Model   : 8bcustom-model

If you use the local deployment name from the original DGX runtime:

Model: dgx-stable-current

If host.docker.internal does not work in your Docker environment, try:

Base URL: http://172.17.0.1:8000/v1

Example prompts

Korean developer support:

Ubuntu에서 8000 포트를 사용 중인 프로세스를 확인하고 종료하는 절차를 알려주세요.

vLLM troubleshooting:

vLLM 서버가 Open-WebUI에 모델을 표시하지 못할 때 확인해야 할 순서를 알려주세요.

LoRA workflow:

LoRA adapter를 merge한 뒤 vLLM에서 서빙하기 전 확인해야 할 파일 목록을 알려주세요.

Dataset validation:

JSONL 학습 데이터에서 깨진 JSON과 중복 instruction을 검사하는 Python 스크립트를 만들어주세요.

Intended use

This release is intended for:

Local developer assistants
On-premise coding assistant experiments
vLLM/Open-WebUI deployment practice
Korean-language coding support
LoRA and dataset pipeline testing

Out-of-scope use

This model is not intended to be treated as a fully audited security, legal, medical, or financial advisor. Operational outputs should be reviewed before applying them to production systems.

Deployment notes

The original local deployment used:

text

Local served model name: dgx-stable-current
Open-WebUI URL        : http://127.0.0.1:3000
vLLM URL              : http://127.0.0.1:8000/v1
Open-WebUI Base URL   : http://host.docker.internal:8000/v1

The public release name is:

8bcustom-model

Project highlights

This project demonstrates an end-to-end local LLM workflow:

Dataset filtering and repair
LoRA candidate testing
Regression rejection
Stable adapter preservation
Model merge for vLLM
Open-WebUI integration
systemd autostart
Private backup upload
Public Hugging Face release
Runtime route/template hardening

Collaboration

This repository can be used as a portfolio reference for:

Local LLM deployment
vLLM serving
Open-WebUI integration
Korean coding assistant customization
LoRA fine-tuning and repair workflows
On-premise AI assistant setup

For collaboration, please contact through the Hugging Face profile associated with this repository.

Disclaimer

This is an experimental local LLM deployment release. Validate outputs before use in production environments.

koreallmdev/8bcustom-model

Legacy / Experimental Release

8bcustom-model