dalle-mini
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vqgan_imagenet_f16_16384

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vqgan_imagenet_f16_16384 / uncertain

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b4c1a77 almost 2 years ago

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	import sagemaker
	import boto3
	from sagemaker.huggingface import HuggingFace

	# gets role for executing training job
	iam_client = boto3.client('iam')
	role = iam_client.get_role(RoleName='{IAM_ROLE_WITH_SAGEMAKER_PERMISSIONS}')['Role']['Arn']
	hyperparameters = {
	'model_name_or_path':'dalle-mini/vqgan_imagenet_f16_16384',
	'output_dir':'/opt/ml/model'
	# add your remaining hyperparameters
	# more info here https://github.com/huggingface/transformers/tree/v4.17.0/examples/pytorch/language-modeling
	}

	# git configuration to download our fine-tuning script
	git_config = {'repo': 'https://github.com/huggingface/transformers.git','branch': 'v4.17.0'}

	# creates Hugging Face estimator
	huggingface_estimator = HuggingFace(
	entry_point='run_mlm.py',
	source_dir='./examples/pytorch/language-modeling',
	instance_type='ml.p3.2xlarge',
	instance_count=1,
	role=role,
	git_config=git_config,
	transformers_version='4.17.0',
	pytorch_version='1.10.2',
	py_version='py38',
	hyperparameters = hyperparameters
	)

	# starting the train job
	huggingface_estimator.fit()