aws--amazon-sagemaker-examples

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Marco Friaz 1c0826e55b Append the default_bucket_prefix to s3 paths if one exists to hyperparameter_tuning, introduction_to_amazon_algorithms and sagemaker-pipelines sample notebooks (#4807 )

**Description**
This change checks the sagemaker session if there is a default_bucket_prefix set. If a default bucket prefix is specified, it is append it to the s3 path. This was done for hyperparameter_tuning, introduction_to_amazon_algorithms and sagemaker-pipelines sample notebooks. This ensures sample notebooks that utilize s3, works in SageMaker Unified Studio.

Co-authored-by: Marco Friaz <marfriaz@amazon.com>

2025-01-21 09:39:05 -08:00

Amazon_JumpStart_Text_To_Image.ipynb

Append the default_bucket_prefix to s3 paths if one exists to hyperparameter_tuning, introduction_to_amazon_algorithms and sagemaker-pipelines sample notebooks (#4807 )

2025-01-21 09:39:05 -08:00

custom_dog_image_generator.ipynb

Append the default_bucket_prefix to s3 paths if one exists to hyperparameter_tuning, introduction_to_amazon_algorithms and sagemaker-pipelines sample notebooks (#4807 )

2025-01-21 09:39:05 -08:00

JumpStart_Stable_Diffusion_Inference_Only.ipynb

fix: jumpstart example notebook (#4794 )

2024-12-09 10:06:31 -05:00

README.md

JumpStart: changed default id for text to image and added prompt engineering (#3791 )

2023-02-20 13:57:22 -08:00

README.md

SageMaker JumpStart Text to Image

This notebook Amazon_JumpStart_Text_To_Image.ipynb demos how to use JumpStart to generate image conditioned on text that appears indistinguishable from a real images. You can also fine-tune the model on your dataset.