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This repository provides tools to generate a linear algebra dataset and code to train an open-source pre-trained model. Our goal is to explore the model's potential for emergent reasoning, inspired by the Deepseek-R1 paper.

Project description

linalg-zero

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This repository offers tools for generating a linear algebra problem dataset and training an open-source base model, aiming to explore its potential for emergent reasoning as inspired by the Deepseek-R1 paper.

Installation

PyTorch Configuration

This project is configured with PyTorch defaults that work for most users:

  • Linux: CUDA 12.8 builds (for GPU acceleration)
  • macOS/Windows: CPU builds

For Different CUDA Versions

If you need a different CUDA version, run the following commands:

# To automatically detect and install dependencies:
UV_TORCH_BACKEND=auto uv sync

# Alternatively, to install Pytorch with a specific CUDA version:
nvidia-smi                      # check your CUDA version
UV_TORCH_BACKEND=cu121 uv sync  # for CUDA 12.1
UV_TORCH_BACKEND=cu124 uv sync  # for CUDA 12.4
UV_TORCH_BACKEND=cpu uv sync    # for CPU-only

For the available CUDA versions see the official documentation.

Installation

uv venv --python 3.11
source .venv/bin/activate.fish
make install

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