Instructions to use Wwayu/CodeQwen1.5-7B-Chat-mlx-6Bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
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) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
- MLX LM
How to use Wwayu/CodeQwen1.5-7B-Chat-mlx-6Bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "Wwayu/CodeQwen1.5-7B-Chat-mlx-6Bit"
Run an OpenAI-compatible server
# 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"} ] }'
Upload chat_template.jinja with huggingface_hub
Browse files- chat_template.jinja +6 -0
chat_template.jinja
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{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system
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You are a helpful assistant.<|im_end|>
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' }}{% endif %}{{'<|im_start|>' + message['role'] + '
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' + message['content'] + '<|im_end|>' + '
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'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
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' }}{% endif %}
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