lightning-GPT is a minimal wrapper around Andrej Karpathy's minGPT and nanoGPT in Lightning.
It is aimed at providing a minimal Lightning layer on top of minGPT and nanoGPT, while leveraging the full breadth of Lightning.
There are currently a few options:
MinGPT: the GPT model from minGPT vanilla (set--implementation=mingpt)NanoGPT: the GPT model from nanoGPT vanilla (set--implementation=nanogpt)DeepSpeedMinGPT: the GPT model from minGPT made DeepSpeed-ready (set--strategy=deepspeed)DeepSpeedNanoGPT: the GPT model from nanoGPT made DeepSpeed-ready (set--strategy=deepspeed)FSDPMinGPT: the GPT model from minGPT made FSDP (native)-ready (set--strategy=fsdp-gpt)FSDPNanoGPT: the GPT model from nanoGPT made FSDP (native)-ready (set--strategy=fsdp-gpt)
minGPT and nanoGPT are vendored with the repo in the mingpt and nanogpt directories respectively. Find the respective LICENSE there.
Thanks to:
- @karpathy for the original minGPT and nanoGPT implementation
- @williamFalcon for the first Lightning port
- @SeanNaren for the DeepSpeed pieces
There are two main ways to install this package.
Installation from source is preferred if you need the latest version with yet unreleased changes, want to use the provided benchmarking or training suites or need to adjust the package.
Installation from PyPI is preferred if you just want to use a stable version of the package without any modifications.
To install the package, simply run
pip install lightning-gptTo clone the repository, please clone the repo with
git clone https://github.com/Lightning-AI/lightning-GPT && cd lightning-GPT
git submodule update --init --recursiveand install with
pip install -e .After this you can proceed with the following steps.
First install the dependencies
pip install -r requirements.txtthen
python train.pySee
python train.py --helpfor the available flags.
First install the dependencies.
pip install -r requirements.txt
pip install -r requirements/nanogpt.txtthen
python train.pySee
python train.py --helpfor the available flags.
Install the extra-dependencies:
pip install -r requirements/deepspeed.txtand pass the strategy flag to the script
python train.py --implementation mingpt --strategy deepspeedor
python train.py --implementation nanogpt --strategy deepspeedPass the strategy flag to the script
python train.py --implementation mingpt --strategy fsdp_nativeor
python train.py --implementation nanogpt --strategy fsdp_nativeTo run on dynamo/inductor from the PyTorch 2.0 compiler stack, run
python train.py --compile dynamoNote that you will need a recent torch nightly (1.14.x) for torch.compile
to be available.
- https://github.com/karpathy/nanoGPT
- https://github.com/karpathy/minGPT
- https://github.com/SeanNaren/minGPT
- https://pytorch-lightning.readthedocs.io/en/stable/advanced/model_parallel.html
Apache 2.0 license https://opensource.org/licenses/Apache-2.0