Instructions to use Outlier-Ai/Outlier-Lite-7B-MLX-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Outlier-Ai/Outlier-Lite-7B-MLX-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("Outlier-Ai/Outlier-Lite-7B-MLX-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
- Pi new
How to use Outlier-Ai/Outlier-Lite-7B-MLX-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 "Outlier-Ai/Outlier-Lite-7B-MLX-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": "Outlier-Ai/Outlier-Lite-7B-MLX-4bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Outlier-Ai/Outlier-Lite-7B-MLX-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 "Outlier-Ai/Outlier-Lite-7B-MLX-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 Outlier-Ai/Outlier-Lite-7B-MLX-4bit
Run Hermes
hermes
- MLX LM
How to use Outlier-Ai/Outlier-Lite-7B-MLX-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 "Outlier-Ai/Outlier-Lite-7B-MLX-4bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "Outlier-Ai/Outlier-Lite-7B-MLX-4bit" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Outlier-Ai/Outlier-Lite-7B-MLX-4bit", "messages": [ {"role": "user", "content": "Hello"} ] }'
Superseded. This repo is a research artifact from an earlier Outlier lineage and is no longer the recommended download. The current shipping tier is at outlier.host.
Outlier-Lite-7B (MLX 4-bit)
This repo predates the v1.8 Outlier lineup. It is preserved here for reproducibility and historical reference, not as a production recommendation.
What replaced it
Current shipping tiers (see Outlier app v1.8+):
- Outlier Nano 4B — current entry tier
- Outlier Core 27B — current default tier
- Outlier Vision 35B-A3B — current multimodal tier
- DeepSeek-R1-Distill-Qwen-7B — popular reasoning model
- Qwen3-Coder-30B-A3B — popular coding model
For the latest verified benchmarks and downloads, visit outlier.host.
Original notes
This was a research / preview artifact. It may contain experimental adapters, overlays, or quantization variants that did not graduate into the shipping product. Treat any technical claims in earlier revisions of this card as provisional.
License
See YAML frontmatter above. Original license terms preserved.
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