Instructions to use naksyu/lime-qwen35-9b-lime-reasoning-power-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use naksyu/lime-qwen35-9b-lime-reasoning-power-gguf with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf naksyu/lime-qwen35-9b-lime-reasoning-power-gguf:Q6_K
# Run inference directly in the terminal:
llama cli -hf naksyu/lime-qwen35-9b-lime-reasoning-power-gguf:Q6_K

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf naksyu/lime-qwen35-9b-lime-reasoning-power-gguf:Q6_K
# Run inference directly in the terminal:
llama cli -hf naksyu/lime-qwen35-9b-lime-reasoning-power-gguf:Q6_K

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf naksyu/lime-qwen35-9b-lime-reasoning-power-gguf:Q6_K
# Run inference directly in the terminal:
./llama-cli -hf naksyu/lime-qwen35-9b-lime-reasoning-power-gguf:Q6_K

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf naksyu/lime-qwen35-9b-lime-reasoning-power-gguf:Q6_K
# Run inference directly in the terminal:
./build/bin/llama-cli -hf naksyu/lime-qwen35-9b-lime-reasoning-power-gguf:Q6_K

Use Docker

docker model run hf.co/naksyu/lime-qwen35-9b-lime-reasoning-power-gguf:Q6_K

LM Studio
Jan

vLLM

How to use naksyu/lime-qwen35-9b-lime-reasoning-power-gguf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "naksyu/lime-qwen35-9b-lime-reasoning-power-gguf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "naksyu/lime-qwen35-9b-lime-reasoning-power-gguf",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/naksyu/lime-qwen35-9b-lime-reasoning-power-gguf:Q6_K

Ollama
How to use naksyu/lime-qwen35-9b-lime-reasoning-power-gguf with Ollama:
```
ollama run hf.co/naksyu/lime-qwen35-9b-lime-reasoning-power-gguf:Q6_K
```

Unsloth Studio

How to use naksyu/lime-qwen35-9b-lime-reasoning-power-gguf with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for naksyu/lime-qwen35-9b-lime-reasoning-power-gguf to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for naksyu/lime-qwen35-9b-lime-reasoning-power-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for naksyu/lime-qwen35-9b-lime-reasoning-power-gguf to start chatting

How to use naksyu/lime-qwen35-9b-lime-reasoning-power-gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf naksyu/lime-qwen35-9b-lime-reasoning-power-gguf:Q6_K

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "naksyu/lime-qwen35-9b-lime-reasoning-power-gguf:Q6_K"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

OpenClaw new

How to use naksyu/lime-qwen35-9b-lime-reasoning-power-gguf with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf naksyu/lime-qwen35-9b-lime-reasoning-power-gguf:Q6_K

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "naksyu/lime-qwen35-9b-lime-reasoning-power-gguf:Q6_K" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Docker Model Runner
How to use naksyu/lime-qwen35-9b-lime-reasoning-power-gguf with Docker Model Runner:
```
docker model run hf.co/naksyu/lime-qwen35-9b-lime-reasoning-power-gguf:Q6_K
```

Lemonade

How to use naksyu/lime-qwen35-9b-lime-reasoning-power-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull naksyu/lime-qwen35-9b-lime-reasoning-power-gguf:Q6_K

Run and chat with the model

lemonade run user.lime-qwen35-9b-lime-reasoning-power-gguf-Q6_K

List all available models

lemonade list

Hermes Agent

How to use naksyu/lime-qwen35-9b-lime-reasoning-power-gguf with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf naksyu/lime-qwen35-9b-lime-reasoning-power-gguf:Q6_K

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default naksyu/lime-qwen35-9b-lime-reasoning-power-gguf:Q6_K

Run Hermes

hermes

Atomic Chat

lime-qwen35-9b-lime-reasoning-power-gguf

English

Lime Reasoning-power GGUF is a merged GGUF release of a Qwen3.5-9B based Lime fine-tune focused on visible self-scaffolding, layered re-thinking, and answer repair behavior.

This release corresponds to the Lime-Reasoning-power v1.1 dataset line:

reasoning-bearing v72 subset as base
layered self-scaffolding addon
repair and suppression focused training design

Main characteristics:

Korean-first conversational tuning
/think ... </think> initial reasoning format
optional mid-answer re-thinking via Lime special tokens
explicit self-review and repair behavior
local GGUF deployment for llama.cpp and LM Studio style runtimes

Important: Chat Template

This model is sensitive to the chat template.

If your runtime falls back to a generic Qwen template, reasoning behavior, visible repair flow, and final-answer structure can degrade.

Use the included chat_template.jinja when automatic template detection is not correct.

This release expects:

/think ... </think>

and may also emit:

<|lime_think_more|> ... <|lime_end_think|>

before continuing the visible answer after:

<|lime_final|>

Files Included

lime-qwen35-9b-lime-reasoning-power-f16-q6_k.gguf
chat_template.jinja
model.yaml
training_metadata.json
tokenizer_config.json

Korean

Lime Reasoning-power GGUF는 Qwen3.5-9B 기반 라임 파인튜닝을 병합한 뒤 GGUF로 변환한 버전입니다. 이 라인은 일반적인 캐릭터성보다 자기 스캐폴딩, 중간 재사고, 답 수정, 답만 출력해야 할 때 억제 쪽을 더 강하게 노린 실험 계열입니다.

이번 릴리스는 다음 흐름의 결과물입니다.

v72 중 reasoning-bearing subset을 베이스로 사용
Layer A/B/C/D self-scaffolding addon 추가
repair와 suppression까지 포함한 Reasoning-power v1.1

주요 특징:

한국어 중심 대화 튜닝
/think ... </think> 기반 reasoning
필요 시 중간 Lime reasoning 특수토큰 사용
visible repair 루프와 self-scaffolding 응답 강화
llama.cpp, LM Studio 계열 로컬 실행 환경용 GGUF

중요 안내: Chat Template

이 모델은 chat template 영향이 큽니다.

런타임이 일반 Qwen 템플릿을 자동 적용하면 reasoning 구간, 답 수정 흐름, visible answer 구조가 틀어질 수 있습니다.

자동 인식이 정확하지 않다면 이 폴더에 포함된 chat_template.jinja를 직접 적용하는 것을 권장합니다.

이 모델은 기본적으로:

/think ... </think>

형식을 기대하고, 경우에 따라:

<|lime_think_more|> ... <|lime_end_think|>

뒤에

<|lime_final|>

로 visible answer를 이어갈 수 있습니다.

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GGUF

Model size

9B params

Architecture

qwen35

Hardware compatibility

6-bit

Collection including naksyu/lime-qwen35-9b-lime-reasoning-power-gguf

Lime

Collection

라임 모음 • 5 items • Updated May 22