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

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

Broken chat template

by jc2375 - opened Sep 28, 2025

Discussion

jc2375

Sep 28, 2025

Using python scripts (and run_model.sh):
Assistant: [{"name": "get_pricing", "arguments": {"country": "CA", "product_id": 24680}}, {"name": "get_pricing", "arguments": {"country": "CA", "product_id": 13579}}]

🔧 Tool Calls (2):

get_pricing
Arguments: {'country': 'CA', 'product_id': 24680}
get_pricing
Arguments: {'country': 'CA', 'product_id': 13579}

You: get the latest news about AI

Assistant: [{"name": "search_news", "arguments": {"q": "AI", "gl": "us", "lr": "lang_en"}}]

In LMStudio, with included jinja:
User: show me a list of tools available to you and functions you can call
qwen3-4b-toolcalling-codex
[{"name": "list_all_tools", "arguments": {"category": "all"}}, {"name": "get_functions", "arguments": {}}

With manual template changes as noted in the HF model card:
qwen3-4b-toolcalling-codex
[{"name": "list_all_tools", "arguments": {"category": "all"}}, {"name": "get_functions", "arguments": {}}

*Additional characters are being added to the tool calls.

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment