linalg-zero 0.1.0

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.

linalg-zero

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.

• Documentation https://atomwalk12.github.io/linalg-zero/

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.