File size: 5,954 Bytes
787e896 1bd901a 787e896 1bd901a 787e896 c33b9b7 787e896 1bd901a c33b9b7 1bd901a c33b9b7 1bd901a c33b9b7 1bd901a 787e896 1bd901a 787e896 1bd901a 787e896 1bd901a 787e896 1bd901a 787e896 1bd901a 787e896 c33b9b7 787e896 1bd901a 787e896 1bd901a 787e896 1bd901a 787e896 1bd901a c33b9b7 1bd901a c33b9b7 1bd901a c33b9b7 1bd901a 787e896 1bd901a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 | ---
license: other
pipeline_tag: text-generation
tags:
- text-generation
- coding
- korean
- vllm
- open-webui
- local-llm
- lora
- qwen
- 8b
language:
- ko
- en
---
# 8bcustom-model
**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:
```bash
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:
```text
Model: dgx-stable-current
```
If `host.docker.internal` does not work in your Docker environment, try:
```text
Base URL: http://172.17.0.1:8000/v1
```
## Example prompts
Korean developer support:
```text
Ubuntu에서 8000 포트를 사용 중인 프로세스를 확인하고 종료하는 절차를 알려주세요.
```
vLLM troubleshooting:
```text
vLLM 서버가 Open-WebUI에 모델을 표시하지 못할 때 확인해야 할 순서를 알려주세요.
```
LoRA workflow:
```text
LoRA adapter를 merge한 뒤 vLLM에서 서빙하기 전 확인해야 할 파일 목록을 알려주세요.
```
Dataset validation:
```text
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:
```text
8bcustom-model
```
## Project highlights
This project demonstrates an end-to-end local LLM workflow:
1. Dataset filtering and repair
2. LoRA candidate testing
3. Regression rejection
4. Stable adapter preservation
5. Model merge for vLLM
6. Open-WebUI integration
7. systemd autostart
8. Private backup upload
9. Public Hugging Face release
10. 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.
|