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- Retrieve Sagemaker Model from Model Registry in Sagemaker Pipelines
As a workaround, I tried to use from sagemaker workflow lambda_step LambdaStep to retrieve model version ARN and then sagemaker ModelPackage to define sagemaker workflow steps CreateModelStep The minimal working code is the following
- How to use a custome env in a SageMaker Notebook Job?
Instead of deploying image on ECR , you can specify libraries and create environment via lifecycle configuration , as soon as you open your sagemaker notebook instance , your desired env populates After edit: You can use sagemaker studio notebook and attach ecr image to the studio UI here is the reference
- Options for stopping SageMaker endpoint to avoid charges
I followed one of the Amazon SageMaker Examples from GitHub to train a model that would generate images: First I set-up a SageMaker Notebook instance (ml t2 medium), per the instructions Then, opened the running Jupyter notebook, went to SageMaker Examples, and selected one and clicked Use
- python - Sagemaker - No such file or directory - Stack Overflow
from sagemaker import hyperparameters from sagemaker session import TrainingInput from sagemaker estimator
- what is the purpose use for sagemaker config. yaml?
On sagemaker studio, I often get this on the console: sagemaker config INFO - Not applying SDK defaults
- amazon web services - sagemaker notebook instance lifecycle . . .
Finally, you can create a new SageMaker notebook and specify the new start-up script by "changing the environment" as this article explains or leave this script by default However, if you're familiarised with Amazon CDK, then you can simply reuse this sample , where a SageMaker notebook is created with a Lifecycle bash script
- amazon web services - Read and write files in local structure when . . .
Use the SageMaker Python SDK to create the notebook job, in that case, you can pass in the additional files or folders They get uploaded to S3 and available for you when the job is run See a sample notebook here Upload the utils file to S3 and read from S3 in your notebook
- Is there some kind of persistent local storage in aws sagemaker model . . .
SageMaker has a few distinct services in it, and each is optimized for a specific use case If you are talking about the development environment, you are probably using the notebook service The notebook instance is coming with a local EBS (5GB) that you can use to copy some data into it and run the fast development iterations without copying
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