Instructions to use mlx-community/Phi-3-mini-128k-instruct-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Phi-3-mini-128k-instruct-4bit 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/Phi-3-mini-128k-instruct-4bit") 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 mlx-community/Phi-3-mini-128k-instruct-4bit 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/Phi-3-mini-128k-instruct-4bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "mlx-community/Phi-3-mini-128k-instruct-4bit" # 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/Phi-3-mini-128k-instruct-4bit", "messages": [ {"role": "user", "content": "Hello"} ] }'
Memory problems
I tried to summarise ~30k tokens on my M1 Ultra 128GB using the code from model card. It eats up all the memory and I did not have the patience to wait for it to do it, I don't think it would ever do the job. I can summarise the same text with Mixtral 8x22B Q4_K_M way faster and still have some spare memory. What do I do wrong here? Anyone had success with this model and long context?
Hi,
There is an active discussion about this in the mlx GH:
https://github.com/ml-explore/mlx-examples/issues/660
Perhaps you can share this message there and will help shed light into the issue.
Sorry, I don't think it is related. Phi-3-mini is very small model and 4bit does not fit on my 128GB, people in this thread did not complain on VRAM even though Command-R-Plus is much bigger.
ok, could you open a new issue there ?