Text Generation
Safetensors
GGUF
English
qwen3
function-calling
tool-calling
codex
local-llm
4gb-vram
llama-cpp
code-assistant
api-tools
openai-alternative
qwen
instruct
conversational
custom_code
8-bit precision
Instructions to use Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex", filename="Qwen3-4B-Function-Calling-Pro.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex 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 Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex # Run inference directly in the terminal: llama cli -hf Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex # Run inference directly in the terminal: llama cli -hf Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex
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 Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex # Run inference directly in the terminal: ./llama-cli -hf Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex
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 Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex # Run inference directly in the terminal: ./build/bin/llama-cli -hf Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex
Use Docker
docker model run hf.co/Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex
- LM Studio
- Jan
- vLLM
How to use Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex
- Ollama
How to use Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex with Ollama:
ollama run hf.co/Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex
- Unsloth Studio
How to use Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex 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 Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex 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 Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex to start chatting
- Atomic Chat new
- Docker Model Runner
How to use Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex with Docker Model Runner:
docker model run hf.co/Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex
- Lemonade
How to use Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Manojb/Qwen3-4b-toolcall-gguf-llamacpp-codex
Run and chat with the model
lemonade run user.Qwen3-4b-toolcall-gguf-llamacpp-codex-{{QUANT_TAG}}List all available models
lemonade list
| # Qwen3-4B Tool Calling Installation Script | |
| # This script installs all dependencies and sets up the environment | |
| echo "π Qwen3-4B Tool Calling Installation" | |
| echo "=====================================" | |
| # Check if Python is available | |
| if ! command -v python3 &> /dev/null; then | |
| echo "β Python3 not found. Please install Python 3.8+ first." | |
| exit 1 | |
| fi | |
| echo "β Python3 found: $(python3 --version)" | |
| # Check if pip is available | |
| if ! command -v pip3 &> /dev/null; then | |
| echo "β pip3 not found. Please install pip first." | |
| exit 1 | |
| fi | |
| echo "β pip3 found: $(pip3 --version)" | |
| # Install Python dependencies | |
| echo "π¦ Installing Python dependencies..." | |
| pip3 install -r requirements.txt | |
| if [ $? -ne 0 ]; then | |
| echo "β Failed to install Python dependencies" | |
| exit 1 | |
| fi | |
| echo "β Python dependencies installed successfully" | |
| # Check if model file exists | |
| if [ ! -f "Qwen3-4B-Function-Calling-Pro.gguf" ]; then | |
| echo "β οΈ Model file not found: Qwen3-4B-Function-Calling-Pro.gguf" | |
| echo "π₯ Please download the model file from:" | |
| echo " https://huggingface.co/Manojb/qwen3-4b-toolcall-gguf-llamacpp-codex" | |
| echo "" | |
| echo "π‘ You can download it with:" | |
| echo " huggingface-cli download Manojb/qwen3-4b-toolcall-gguf-llamacpp-codex Qwen3-4B-Function-Calling-Pro.gguf" | |
| else | |
| echo "β Model file found: Qwen3-4B-Function-Calling-Pro.gguf" | |
| fi | |
| # Make scripts executable | |
| chmod +x run_model.sh | |
| chmod +x quick_start.py | |
| chmod +x codex_integration.py | |
| echo "β Scripts made executable" | |
| echo "" | |
| echo "π Installation complete!" | |
| echo "" | |
| echo "π Usage:" | |
| echo " ./run_model.sh # Run interactively" | |
| echo " ./run_model.sh server # Start Codex server" | |
| echo " python3 quick_start.py # Quick start demo" | |
| echo " python3 codex_integration.py # Codex integration demo" | |
| echo "" | |
| echo "π For Codex integration:" | |
| echo " 1. Start server: ./run_model.sh server" | |
| echo " 2. Configure Codex with: http://localhost:8000" | |
| echo " 3. Model: Qwen3-4B-Function-Calling-Pro" | |
| echo "" | |
| echo "π³ For Docker deployment:" | |
| echo " docker-compose up -d" | |
| echo "" | |
| echo "Happy coding! π" | |