Instructions to use XformAI-india/Qwen3-0.6B-coders-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 XformAI-india/Qwen3-0.6B-coders-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 XformAI-india/Qwen3-0.6B-coders-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf XformAI-india/Qwen3-0.6B-coders-gguf:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf XformAI-india/Qwen3-0.6B-coders-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf XformAI-india/Qwen3-0.6B-coders-gguf:Q4_K_M

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 XformAI-india/Qwen3-0.6B-coders-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf XformAI-india/Qwen3-0.6B-coders-gguf:Q4_K_M

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 XformAI-india/Qwen3-0.6B-coders-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf XformAI-india/Qwen3-0.6B-coders-gguf:Q4_K_M

Use Docker

docker model run hf.co/XformAI-india/Qwen3-0.6B-coders-gguf:Q4_K_M

LM Studio
Jan
Ollama
How to use XformAI-india/Qwen3-0.6B-coders-gguf with Ollama:
```
ollama run hf.co/XformAI-india/Qwen3-0.6B-coders-gguf:Q4_K_M
```
Unsloth Desktop

How to use XformAI-india/Qwen3-0.6B-coders-gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf XformAI-india/Qwen3-0.6B-coders-gguf:Q4_K_M

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": "XformAI-india/Qwen3-0.6B-coders-gguf:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use XformAI-india/Qwen3-0.6B-coders-gguf with Docker Model Runner:
```
docker model run hf.co/XformAI-india/Qwen3-0.6B-coders-gguf:Q4_K_M
```

Lemonade

How to use XformAI-india/Qwen3-0.6B-coders-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull XformAI-india/Qwen3-0.6B-coders-gguf:Q4_K_M

Run and chat with the model

lemonade run user.Qwen3-0.6B-coders-gguf-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use XformAI-india/Qwen3-0.6B-coders-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 XformAI-india/Qwen3-0.6B-coders-gguf:Q4_K_M

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 XformAI-india/Qwen3-0.6B-coders-gguf:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use XformAI-india/Qwen3-0.6B-coders-gguf with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf XformAI-india/Qwen3-0.6B-coders-gguf:Q4_K_M

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 "XformAI-india/Qwen3-0.6B-coders-gguf:Q4_K_M" \
  --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 Coder – GGUF (Local Use Version)

Model: XformAI-india/qwen3-0.6b-coder-gguf
Base Model: Qwen-0.6B Fine-Tuned On: Code generation tasks
Architecture: Transformer decoder (GPT-style)
Parameter Size: 0.6B (~600M)
Quantization: GGUF (e.g., Q4_K_M / Q6_K)
Converted By: XformAI
Date: May 2025
License: Apache 2.0 (inherited from base)

🚀 Overview

This is the GGUF-converted version of XformAI-india/qwen3-0.6b-coder, optimized for local inference, including:

🔧 llama.cpp
⚙️ LM Studio
💻 Ollama
🐍 KoboldCpp / text-generation-webui

It is trained for task-oriented code generation, covering Python, Bash, HTML, JavaScript, and small app scaffolding.

🧱 Model Details

Feature	Value
Model Format	GGUF (Q4, Q5, Q6, etc.)
Model Type	Decoder-only LLM
Base	Qwen 0.5B
Fine-Tune Method	LoRA (code-tasks)
File Sizes	Q4_K_M: ~460MB / Q6: ~800MB
Context Length	2048 tokens
Tokenizer	Compatible with Qwen tokenizer (`qwen.tiktoken`)

🛠 Use Cases

Lightweight local coding assistants
VSCode extensions
CLI & DevOps helpers
Edge AI programming bots
Offline developer tools

💻 How to Use (locally with `llama.cpp`)

# Clone llama.cpp if not already
git clone https://github.com/ggerganov/llama.cpp
cd llama.cpp
make

# Run the model
./main -m qwen-0.6b-coder.Q4_K_M.gguf -p "Write a Python script that creates a zip file from a directory."

Downloads last month: 327

GGUF

Model size

0.6B params

Architecture

qwen3

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for XformAI-india/Qwen3-0.6B-coders-gguf

Base model

Qwen/Qwen3-0.6B-Base

Finetuned

Qwen/Qwen3-0.6B

Quantized

(453)

this model

💻 Qwen3-0.6B Coder – GGUF (Local Use Version)

🚀 Overview

🧱 Model Details

🛠 Use Cases

💻 How to Use (locally with llama.cpp)

Model tree for XformAI-india/Qwen3-0.6B-coders-gguf

💻 How to Use (locally with `llama.cpp`)