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Description:

lightninggpt 0.1.1

lightning-GPT
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

Installation
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.
Installation from PyPI
To install the package, simply run
pip install lightning-gpt

Installation from source
To clone the repository, please clone the repo with
git clone https://github.com/Lightning-AI/lightning-GPT && cd lightning-GPT
git submodule update --init --recursive

and install with
pip install -e .

After this you can proceed with the following steps.
MinGPT
First install the dependencies
pip install -r requirements.txt

then
python train.py

See
python train.py --help

for the available flags.
NanoGPT
First install the dependencies.
pip install -r requirements.txt
pip install -r requirements/nanogpt.txt

then
python train.py

See
python train.py --help

for the available flags.
DeepSpeed
Install the extra-dependencies:
pip install -r requirements/deepspeed.txt

and pass the strategy flag to the script
python train.py --implementation mingpt --strategy deepspeed

or
python train.py --implementation nanogpt --strategy deepspeed

FSDP native
Pass the strategy flag to the script
python train.py --implementation mingpt --strategy fsdp_native

or
python train.py --implementation nanogpt --strategy fsdp_native

PyTorch 2.0
To run on dynamo/inductor from the PyTorch 2.0 compiler stack, run
python train.py --compile dynamo

Note that you will need a recent torch nightly (1.14.x) for torch.compile
to be available.
Credits

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

License
Apache 2.0 license https://opensource.org/licenses/Apache-2.0