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Update README.md

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@@ -10,37 +10,4 @@ tags:
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  - art
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  size_categories:
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  - n>1T
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- ---
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- import sagemaker
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- import boto3
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- from sagemaker.huggingface import HuggingFace
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-
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- # gets role for executing training job
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- iam_client = boto3.client('iam')
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- role = iam_client.get_role(RoleName='{IAM_ROLE_WITH_SAGEMAKER_PERMISSIONS}')['Role']['Arn']
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- hyperparameters = {
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- 'model_name_or_path':'databricks/dolly-v2-12b',
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- 'output_dir':'/opt/ml/model'
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- # add your remaining hyperparameters
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- # more info here https://github.com/huggingface/transformers/tree/v4.17.0/examples/pytorch/question-answering
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- }
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-
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- # git configuration to download our fine-tuning script
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- git_config = {'repo': 'https://github.com/huggingface/transformers.git','branch': 'v4.17.0'}
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-
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- # creates Hugging Face estimator
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- huggingface_estimator = HuggingFace(
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- entry_point='run_qa.py',
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- source_dir='./examples/pytorch/question-answering',
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- instance_type='ml.p3.2xlarge',
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- instance_count=1,
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- role=role,
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- git_config=git_config,
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- transformers_version='4.17.0',
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- pytorch_version='1.10.2',
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- py_version='py38',
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- hyperparameters = hyperparameters
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- )
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-
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- # starting the train job
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- huggingface_estimator.fit()
 
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  - art
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  size_categories:
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  - n>1T
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+ ---