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Installation

From PyPI

pip install lmxlab

From source (development)

git clone https://github.com/michaelellis003/lmxlab.git
cd lmxlab
pip install -e ".[dev]"

Requirements

  • Python 3.12+
  • Apple Silicon Mac (M1/M2/M3/M4) for GPU acceleration

MLX also runs on Intel Macs and Linux using CPU, but performance will differ.

Optional dependencies

Install extras for additional functionality:

# BPE tokenization (tiktoken)
pip install lmxlab[tokenizers]

# HuggingFace model loading
pip install lmxlab[hf]

# Experiment tracking (MLflow)
pip install lmxlab[experiments]

# Everything for development
pip install -e ".[dev]"

Verify installation

import mlx.core as mx
from lmxlab.models.gpt import gpt_tiny
from lmxlab.models.base import LanguageModel

config = gpt_tiny()
model = LanguageModel(config)
mx.eval(model.parameters())

tokens = mx.array([[1, 2, 3, 4]])
logits, _ = model(tokens)
mx.eval(logits)
print(f"Output shape: {logits.shape}")  # (1, 4, vocab_size)
print("Installation OK!")

Or use the CLI:

lmxlab list

Troubleshooting

ImportError: libmlx.so on Linux/Intel Mac: MLX requires Apple Silicon for GPU support. On other platforms it falls back to CPU, but the shared library must still be available. Ensure mlx>=0.25 is installed correctly: pip install mlx.

ModuleNotFoundError: No module named 'tiktoken': Install the tokenizers extra: pip install lmxlab[tokenizers].

Slow first run: MLX compiles computation graphs on first execution. Subsequent runs are faster. This is expected behavior.