Instructions to use mlx-community/Qwen2.5-32B-Instruct-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mlx-community/Qwen2.5-32B-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/Qwen2.5-32B-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 Settings
LM Studio

How to use mlx-community/Qwen2.5-32B-Instruct-4bit with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "mlx-community/Qwen2.5-32B-Instruct-4bit"

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "mlx-lm": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "mlx-community/Qwen2.5-32B-Instruct-4bit"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use mlx-community/Qwen2.5-32B-Instruct-4bit with Hermes Agent:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "mlx-community/Qwen2.5-32B-Instruct-4bit"

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default mlx-community/Qwen2.5-32B-Instruct-4bit

Run Hermes

hermes

MLX LM

How to use mlx-community/Qwen2.5-32B-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/Qwen2.5-32B-Instruct-4bit"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "mlx-community/Qwen2.5-32B-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/Qwen2.5-32B-Instruct-4bit",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Bug fix for the tool use chat template.

by jfaiofj92459 - opened Mar 3, 2025

base: refs/heads/main

←

from: refs/pr/2

Discussion Files changed

-1

jfaiofj92459

MLX Community org Mar 3, 2025

•

edited Mar 3, 2025

The chat template provides an example for how tool use should be formatted. In the current version of the tokenizer_config file, these tools are mistakenly wrapped in double curly braces. This confuses smaller models (tested on the 14B and 7B versions).

The proposed changed also matches the original chat template in the official Qwen2.5 repo, see: https://huggingface.co/Qwen/Qwen2.5-32B-Instruct/blob/main/tokenizer_config.json

Bug fix for the tool use chat template.948f13dc

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