Instructions to use zerolimites/Qwen3-0.6B-Code-Surgery-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use zerolimites/Qwen3-0.6B-Code-Surgery-v2 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 zerolimites/Qwen3-0.6B-Code-Surgery-v2:F16
# Run inference directly in the terminal:
llama cli -hf zerolimites/Qwen3-0.6B-Code-Surgery-v2:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf zerolimites/Qwen3-0.6B-Code-Surgery-v2:F16
# Run inference directly in the terminal:
llama cli -hf zerolimites/Qwen3-0.6B-Code-Surgery-v2:F16

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf zerolimites/Qwen3-0.6B-Code-Surgery-v2:F16
# Run inference directly in the terminal:
./build/bin/llama cli -hf zerolimites/Qwen3-0.6B-Code-Surgery-v2:F16

Use Docker

docker model run hf.co/zerolimites/Qwen3-0.6B-Code-Surgery-v2:F16

Llama new
LM Studio
Jan

vLLM

How to use zerolimites/Qwen3-0.6B-Code-Surgery-v2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "zerolimites/Qwen3-0.6B-Code-Surgery-v2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zerolimites/Qwen3-0.6B-Code-Surgery-v2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/zerolimites/Qwen3-0.6B-Code-Surgery-v2:F16

Ollama
How to use zerolimites/Qwen3-0.6B-Code-Surgery-v2 with Ollama:
```
ollama run hf.co/zerolimites/Qwen3-0.6B-Code-Surgery-v2:F16
```
Unsloth Desktop

How to use zerolimites/Qwen3-0.6B-Code-Surgery-v2 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf zerolimites/Qwen3-0.6B-Code-Surgery-v2:F16

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "zerolimites/Qwen3-0.6B-Code-Surgery-v2:F16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use zerolimites/Qwen3-0.6B-Code-Surgery-v2 with Docker Model Runner:
```
docker model run hf.co/zerolimites/Qwen3-0.6B-Code-Surgery-v2:F16
```

Lemonade

How to use zerolimites/Qwen3-0.6B-Code-Surgery-v2 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull zerolimites/Qwen3-0.6B-Code-Surgery-v2:F16

Run and chat with the model

lemonade run user.Qwen3-0.6B-Code-Surgery-v2-F16

List all available models

lemonade list

Hermes Agent

How to use zerolimites/Qwen3-0.6B-Code-Surgery-v2 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf zerolimites/Qwen3-0.6B-Code-Surgery-v2:F16

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 zerolimites/Qwen3-0.6B-Code-Surgery-v2:F16

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use zerolimites/Qwen3-0.6B-Code-Surgery-v2 with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf zerolimites/Qwen3-0.6B-Code-Surgery-v2:F16

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 "zerolimites/Qwen3-0.6B-Code-Surgery-v2:F16" \
  --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"

💻 Qwen3-0.6B-Code-Surgery-v2 (Safetensors + GGUF Q8_0 & F16 — 96.43% Pass@1)

Qwen3-0.6B-Code-Surgery-v2 é a versão editada diretamente nos pesos de Qwen/Qwen3-0.6B para programação poliglota (Python, Linux/Bash, Web HTML/CSS/JS e Sistemas C/Rust/Go/SQL), combinando Projeção Ortogonal de Comentários (P_comm) + Injeção Associativa MEMIT no Espaço Nulo + Polimento Iterativo de Margem nas Camadas 20 a 27.

Este repositório inclui o modelo padrão Hugging Face (model.safetensors) e as versões GGUF (Q8_0 8-bit e F16 16-bit).

📊 Resultados no Benchmark Executável de Código (28 Problemas)

Modelo	Passaram / Total	Precisão Geral (%)	Python (`PY`)	Linux/Bash (`LINUX`)	Web (`WEB`)	Sistemas (`SYS`)
`Qwen/Qwen3-0.6B` (Base Normal)	`13 / 28`	46.43%	`1/7` (14.29%)	`4/7` (57.14%)	`4/7` (57.14%)	`4/7` (57.14%)
`Qwen3-0.6B` (Stage 1 `P_comm`)	`14 / 28`	50.00%	`2/7` (28.57%)	`4/7` (57.14%)	`4/7` (57.14%)	`4/7` (57.14%)
`Qwen3-0.6B` (Editado v1)	`24 / 28`	85.71%	`5/7` (71.43%)	`7/7` (100.00%)	`6/7` (85.71%)	`6/7` (85.71%)
`Qwen3-0.6B-Code-Surgery-v2` (Final)	`27 / 28`	96.43%	`7/7` (100.00%)	`7/7` (100.00%)	`6/7` (85.71%)	`7/7` (100.00%)

📦 Arquivos Disponíveis

model.safetensors (1.51 GB — bfloat16): Modelo Hugging Face completo.
Qwen3-0.6B-Code-Surgery-v2-Q8_0.gguf (804 MB — Q8_0): Modelo GGUF quantizado em 8-bit.
Qwen3-0.6B-Code-Surgery-v2-F16.gguf (1.51 GB — F16): Modelo GGUF em 16-bit.
Modelfile: Pronto para importar no Ollama.
code_comparison_complete.json: Comparação completa de todas as 4 etapas nas 28 tarefas.

Downloads last month: 57

Safetensors

Model size

0.8B params

Tensor type

BF16

Model tree for zerolimites/Qwen3-0.6B-Code-Surgery-v2

Base model

Qwen/Qwen3-0.6B-Base

Finetuned

Qwen/Qwen3-0.6B

Quantized

(529)

this model

zerolimites
/

Qwen3-0.6B-Code-Surgery-v2

💻 Qwen3-0.6B-Code-Surgery-v2 (Safetensors + GGUF Q8_0 & F16 — 96.43% Pass@1)

📊 Resultados no Benchmark Executável de Código (28 Problemas)

📦 Arquivos Disponíveis

Model tree for zerolimites/Qwen3-0.6B-Code-Surgery-v2

Spaces using zerolimites/Qwen3-0.6B-Code-Surgery-v2 4