How to use Wwayu/CodeQwen1.5-7B-Chat-mlx-6Bit 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("Wwayu/CodeQwen1.5-7B-Chat-mlx-6Bit") 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)
How to use Wwayu/CodeQwen1.5-7B-Chat-mlx-6Bit with MLX LM:
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "Wwayu/CodeQwen1.5-7B-Chat-mlx-6Bit"
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "Wwayu/CodeQwen1.5-7B-Chat-mlx-6Bit" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Wwayu/CodeQwen1.5-7B-Chat-mlx-6Bit", "messages": [ {"role": "user", "content": "Hello"} ] }'
https://huggingface.co/Wwayu/CodeQwen1.5-7B-Chat-mlx-6Bit/resolve/main/tokenizer.json
hf download hf://Wwayu/CodeQwen1.5-7B-Chat-mlx-6Bit/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/Wwayu/CodeQwen1.5-7B-Chat-mlx-6Bit/resolve/main/tokenizer.json
