Libraries MLX How to use madroid/Qwen1.5-0.5B with MLX:
# Make sure mlx-lm is installed
# pip install --upgrade mlx-lm
# Generate text with mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("madroid/Qwen1.5-0.5B")
prompt = "Write a story about Einstein"
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True
)
text = generate(model, tokenizer, prompt=prompt, verbose=True) Notebooks Google Colab Kaggle Local Apps Settings llama.cpp How to use madroid/Qwen1.5-0.5B 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 madroid/Qwen1.5-0.5B:Q4_0
# Run inference directly in the terminal:
llama cli -hf madroid/Qwen1.5-0.5B:Q4_0 Install from WinGet (Windows) winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf madroid/Qwen1.5-0.5B:Q4_0
# Run inference directly in the terminal:
llama cli -hf madroid/Qwen1.5-0.5B:Q4_0 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 madroid/Qwen1.5-0.5B:Q4_0
# Run inference directly in the terminal:
./llama-cli -hf madroid/Qwen1.5-0.5B:Q4_0 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 madroid/Qwen1.5-0.5B:Q4_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf madroid/Qwen1.5-0.5B:Q4_0 Use Docker docker model run hf.co/madroid/Qwen1.5-0.5B:Q4_0 LM Studio Jan vLLM How to use madroid/Qwen1.5-0.5B with vLLM:
Install from pip and serve model # Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "madroid/Qwen1.5-0.5B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "madroid/Qwen1.5-0.5B",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}' Use Docker docker model run hf.co/madroid/Qwen1.5-0.5B:Q4_0 Ollama How to use madroid/Qwen1.5-0.5B with Ollama:
ollama run hf.co/madroid/Qwen1.5-0.5B:Q4_0 Unsloth Studio How to use madroid/Qwen1.5-0.5B 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 madroid/Qwen1.5-0.5B 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 madroid/Qwen1.5-0.5B to start chatting Using HuggingFace Spaces for Unsloth # No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for madroid/Qwen1.5-0.5B to start chatting Atomic Chat new MLX LM How to use madroid/Qwen1.5-0.5B with MLX LM:
Generate or start a chat session # Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "madroid/Qwen1.5-0.5B" Run an OpenAI-compatible server # Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "madroid/Qwen1.5-0.5B"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "madroid/Qwen1.5-0.5B",
"messages": [
{"role": "user", "content": "Hello"}
]
}' Docker Model Runner How to use madroid/Qwen1.5-0.5B with Docker Model Runner:
docker model run hf.co/madroid/Qwen1.5-0.5B:Q4_0 Lemonade How to use madroid/Qwen1.5-0.5B with Lemonade:
Pull the model # Download Lemonade from https://lemonade-server.ai/
lemonade pull madroid/Qwen1.5-0.5B:Q4_0 Run and chat with the model lemonade run user.Qwen1.5-0.5B-Q4_0 List all available models lemonade list 
Install Unsloth Studio (macOS, Linux, WSL)
# Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for madroid/Qwen1.5-0.5B to start chatting