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Foundation for modern ML research

Project description

fabrique

fabrique provides foundation components for ML research in LLM/VLM space, including:

  • model implementations
  • fine-tuning routines and examples
  • multi-GPU execution
  • interoperability with broader ecosystem

fabrique is written in JAX/Flax NNX and follows their philosophy.

Installation

You can install the latest released version of fabrique from PYPI:

pip install fabrique

Alternatively, you can mount the development version of fabrique directly to your project and use existing code as reference for your own models:

cd /path/to/your/project

# clone the repository
mkdir lib
git clone https://github.com/ridcl/fabrique lib/fabrique

# or even add it as a submodule
# git submodule add git@github.com:ridlc/fabrique.git lib/fabrique

# set up PYTHONPATH to include fabrique as a package
export PYTHONPATH=${PYTHONPATH}:lib/fabrique/src

Usage

TODO

Model support

As of now, fabrique focuses on Gemma as its primary LLM/VLM implementation. Previously, fabrique also supported Llama 3, Phi 3/4 and Qwen 2.5. You can find these old implementations in legacy/src/fabrique/models.

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