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ColossalAI/examples/language/gpt/titans
Hongxin Liu 7f8b16635b
[misc] refactor launch API and tensor constructor (#5666)
7 months ago
..
configs
dataset
model [npu] change device to accelerator api (#5239) 11 months ago
LICENSE
README.md
requirements.txt
run.sh
test_ci.sh
train_gpt.py [misc] refactor launch API and tensor constructor (#5666) 7 months ago

README.md

Run GPT With Colossal-AI

How to Prepare Webtext Dataset

You can download the preprocessed sample dataset for this demo via our Google Drive sharing link.

You can also avoid dataset preparation by using --use_dummy_dataset during running.

Run this Demo

Use the following commands to install prerequisites.

# assuming using cuda 11.3
pip install -r requirements.txt

Use the following commands to execute training.

#!/usr/bin/env sh
# if you want to use real dataset, then remove --use_dummy_dataset
# export DATA=/path/to/small-gpt-dataset.json'

# run on a single node
colossalai run --nproc_per_node=<num_gpus> train_gpt.py --config configs/<config_file> --from_torch --use_dummy_dataset

# run on multiple nodes
colossalai run --nproc_per_node=<num_gpus> \
   --master_addr <hostname> \
   --master_port <port-number> \
   --hosts <list-of-hostname-separated-by-comma> \
   train_gpt.py \
   --config configs/<config_file> \
   --from_torch \
   --use_dummy_dataset

# run on multiple nodes with slurm
srun python \
   train_gpt.py \
   --config configs/<config_file> \
   --host <master_node> \
   --use_dummy_dataset

You can set the <config_file> to any file in the configs folder. To simply get it running, you can start with gpt_small_zero3_pp1d.py on a single node first. You can view the explanations in the config file regarding how to change the parallel setting.