Instructions to use mlx-community/Apertus-8B-Instruct-2509-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Apertus-8B-Instruct-2509-8bit 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/Apertus-8B-Instruct-2509-8bit") 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
- Pi
How to use mlx-community/Apertus-8B-Instruct-2509-8bit 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/Apertus-8B-Instruct-2509-8bit"
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/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/Apertus-8B-Instruct-2509-8bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- MLX LM
How to use mlx-community/Apertus-8B-Instruct-2509-8bit 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/Apertus-8B-Instruct-2509-8bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "mlx-community/Apertus-8B-Instruct-2509-8bit" # 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/Apertus-8B-Instruct-2509-8bit", "messages": [ {"role": "user", "content": "Hello"} ] }' - Hermes Agent
How to use mlx-community/Apertus-8B-Instruct-2509-8bit 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/Apertus-8B-Instruct-2509-8bit"
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/Apertus-8B-Instruct-2509-8bit
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use mlx-community/Apertus-8B-Instruct-2509-8bit with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "mlx-community/Apertus-8B-Instruct-2509-8bit"
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "mlx-community/Apertus-8B-Instruct-2509-8bit" \ --custom-provider-id mlx-lm \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
mlx-community/Apertus-8B-Instruct-2509-8bit doesn't work on Google Colaboratory
From the code:
! pip install --upgrade mlx-lm &>/dev/null
from mlx_lm import load, generate
I have the following error:
"""
ImportError Traceback (most recent call last)
/tmp/ipython-input-173744910.py in <cell line: 0>()
----> 1 from mlx_lm import load, generate
2
1 frames
/usr/local/lib/python3.12/dist-packages/mlx_lm/convert.py in
5 from typing import Callable, Optional, Union
6
----> 7 import mlx.core as mx
8 import mlx.nn as nn
9 from mlx.utils import tree_map_with_path
ImportError: libmlx.so: cannot open shared object file: No such file or directory
NOTE: If your import is failing due to a missing package, you can
manually install dependencies using either !pip or !apt.
To view examples of installing some common dependencies, click the
"Open Examples" button below.
"""
Isn't MLX only for Apple Silicon? Meaning it won't run on any hardware other than apple silicon.
Ah ok, I didn't know that MLX works only for Apple. Thank you