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Fix typos&expressions
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haohanchen-aws committed Oct 12, 2022
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"cell_type": "markdown",
"metadata": {},
"source": [
"This notebook walks you through how to use the tensor parallelism feature provided by the SageMaker model parallelism library. You'll learn how to train the GPT-J model with tensor parallelism on the GLUE sst2 dataset.\n",
"This notebook walks you through how to use the tensor parallelism feature provided by the SageMaker model parallelism library. You'll learn how to run FP16 training of the GPT-J model with tensor parallelism on the GLUE sst2 dataset.\n",
"\n",
"## Install and Upgrade Libraries\n",
"\n",
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"cell_type": "markdown",
"metadata": {},
"source": [
"### Create a SageMaker HuggingFace 🤗 Estimator\n",
"### Create a SageMaker PyTorch Estimator\n",
"\n",
"The following cell constructs a PyTorch estimator using the parameters defined above. To see how the SageMaker tensor parallelism modules and functions are applied to the script, see the `train_gptj_smp_tensor_parallel_script.py` file and the private preview documentation. "
]
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"- `requirements.txt`: This will install the dependencies, like the right version of huggingface transformers.\n",
"- `data_prep_512.py`: This will download and preprocess the openwebtext dataset.\n",
"- `memory_tracker.py`: This contains the functions to track memory usage.\n",
"- `sharded_data_parallel_checkpoint.py`: This contains the checkpoint utils for sharded dat parallelism\n",
"- `sharded_data_parallel_checkpoint.py`: This contains checkpoint util functions for sharded data parallelism\n",
"\n",
"### Additional Resources\n",
"If you are a new user of Amazon SageMaker, you may find the following helpful to learn more about SMP and using SageMaker with PyTorch.\n",
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"cell_type": "markdown",
"metadata": {},
"source": [
"### Create a SageMaker HuggingFace Estimator\n",
"### Create a SageMaker PyTorch Estimator\n",
"\n",
"The following cell constructs a HuggingFace estimator using the parameters defined above. To see how the SageMaker tensor parallelism modules and functions are applied to the script, see the `train_gpt_simple.py` file."
"The following cell constructs a PyTorch estimator using the parameters defined above. To see how the SageMaker tensor parallelism modules and functions are applied to the script, see the `train_gpt_simple.py` file."
]
},
{
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