Instructions to use mlx-community/Qwen2-Math-72B-Instruct-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Qwen2-Math-72B-Instruct-bf16 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("mlx-community/Qwen2-Math-72B-Instruct-bf16") 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
- LM Studio
- MLX LM
How to use mlx-community/Qwen2-Math-72B-Instruct-bf16 with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "mlx-community/Qwen2-Math-72B-Instruct-bf16"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "mlx-community/Qwen2-Math-72B-Instruct-bf16" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mlx-community/Qwen2-Math-72B-Instruct-bf16", "messages": [ {"role": "user", "content": "Hello"} ] }'
752b712266d9080cb7010045e5397627671e40a7c6fff79f412dc2a901be25d0
Browse files
model-00013-of-00028.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:af3f4e795ee002c5611dcf76227393680223c86e4ede921a6a075550b06a2e9c
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size 5266112588
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