# Example notebooks
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For step-by-step examples on how to use publicly available JumpStart foundation models with the SageMaker Python SDK, refer to the following notebooks on text generation, image generation, and model customization.

**Note**  
Proprietary and publicly available JumpStart foundation models have different SageMaker AI Python SDK deployment workflows. Discover proprietary foundation model example notebooks through Amazon SageMaker Studio Classic or the SageMaker AI console. For more information, see [JumpStart foundation model usage](jumpstart-foundation-models-use.md).

You can clone the [Amazon SageMaker AI examples repository](https://github.com/aws/amazon-sagemaker-examples/tree/main/introduction_to_amazon_algorithms/jumpstart-foundation-models) to run the available JumpStart foundation model examples in the Jupyter environment of your choice within Studio. For more information on applications that you can use to create and access Jupyter in SageMaker AI, see [Applications supported in Amazon SageMaker Studio](studio-updated-apps.md).

## Time series forecasting
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You can use the Chronos models to forecast time series data. They're based on the language model architecture. Use the [Introduction to SageMaker JumpStart - Time Series Forecasting with Chronos](https://github.com/aws/amazon-sagemaker-examples/blob/default/%20%20%20%20generative_ai/sm-jumpstart_time_series_forecasting.ipynb) notebook to get started.

For information about the available Chronos models, see [Available foundation models](jumpstart-foundation-models-latest.md).

## Text generation
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Explore text generation example notebooks, including guidance on general text generation workflows, multilingual text classification, real-time batch inference, few-shot learning, chatbot interactions, and more. 
+ [SageMaker JumpStart Foundation Models - HuggingFace Text2Text Generation with FLAN-T5 XL as an example](https://sagemaker-examples.readthedocs.io/en/latest/introduction_to_amazon_algorithms/jumpstart-foundation-models/text2text-generation-flan-t5.html)
+ [SageMaker JumpStart Foundation Models - BloomZ: Multilingual Text Classification, Question and Answering, Code Generation, Paragraph rephrase, and More](https://sagemaker-examples.readthedocs.io/en/latest/introduction_to_amazon_algorithms/jumpstart-foundation-models/text2text-generation-bloomz.html)
+ [SageMaker JumpStart Foundation Models - HuggingFace Text2Text Generation Batch Transform and Real-Time Batch Inference](https://sagemaker-examples.readthedocs.io/en/latest/introduction_to_amazon_algorithms/jumpstart-foundation-models/text2text-generation-Batch-Transform.html)
+ [SageMaker JumpStart Foundation Models - GPT-J, GPT-Neo Few-shot learning](https://sagemaker-examples.readthedocs.io/en/latest/introduction_to_amazon_algorithms/jumpstart-foundation-models/text-generation-few-shot-learning.html)
+ [SageMaker JumpStart Foundation Models - Chatbots](https://sagemaker-examples.readthedocs.io/en/latest/introduction_to_amazon_algorithms/jumpstart-foundation-models/text-generation-chatbot.html)
+ [Introduction to SageMaker JumpStart - Text Generation with Mistral models](https://sagemaker-examples.readthedocs.io/en/latest/introduction_to_amazon_algorithms/jumpstart-foundation-models/mistral-7b-instruction-domain-adaptation-finetuning.html)
+ [Introduction to SageMaker JumpStart - Text Generation with Falcon models](https://sagemaker-examples.readthedocs.io/en/latest/introduction_to_amazon_algorithms/jumpstart-foundation-models/falcon-7b-instruction-domain-adaptation-finetuning.html)

## Image generation
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Get started with text-to-image Stable Diffusion models, learn how to deploy an inpainting model, and experiment with a simple workflow to generate images of your dog. 
+ [Introduction to JumpStart - Text to Image](https://sagemaker-examples.readthedocs.io/en/latest/introduction_to_amazon_algorithms/jumpstart_text_to_image/Amazon_JumpStart_Text_To_Image.html)
+ [Introduction to JumpStart Image editing - Stable Diffusion Inpainting](https://sagemaker-examples.readthedocs.io/en/latest/introduction_to_amazon_algorithms/jumpstart_inpainting/Amazon_JumpStart_Inpainting.html)
+ [Generate fun images of your dog](https://sagemaker-examples.readthedocs.io/en/latest/introduction_to_amazon_algorithms/jumpstart_text_to_image/custom_dog_image_generator.html)

## Model customization
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Sometimes your use case requires greater foundation model customization for specific tasks. For more information on model customization approaches, see [Foundation model customization](jumpstart-foundation-models-customize.md) or explore one of the following example notebooks. 
+ [SageMaker JumpStart Foundation Models - Fine-tuning text generation GPT-J 6B model on domain specific dataset](https://sagemaker-examples.readthedocs.io/en/latest/introduction_to_amazon_algorithms/jumpstart-foundation-models/domain-adaption-finetuning-gpt-j-6b.html)
+ [SageMaker JumpStart Foundation Models - HuggingFace Text2Text Instruction Fine-Tuning](https://sagemaker-examples.readthedocs.io/en/latest/introduction_to_amazon_algorithms/jumpstart-foundation-models/instruction-fine-tuning-flan-t5.html)
+ [Retrieval-Augmented Generation: Question Answering using LangChain and Cohere’s Generate and Embedding Models from SageMaker JumpStart](https://sagemaker-examples.readthedocs.io/en/latest/introduction_to_amazon_algorithms/jumpstart-foundation-models/question_answering_retrieval_augmented_generation/question_answering_Cohere+langchain_jumpstart.html)
+ [Retrieval-Augmented Generation: Question Answering using LLama-2, Pinecone and Custom Dataset](https://sagemaker-examples.readthedocs.io/en/latest/introduction_to_amazon_algorithms/jumpstart-foundation-models/question_answering_retrieval_augmented_generation/question_answering_pinecone_llama-2_jumpstart.html)
+ [Retrieval-Augmented Generation: Question Answering based on Custom Dataset with Open-sourced LangChain Library](https://sagemaker-examples.readthedocs.io/en/latest/introduction_to_amazon_algorithms/jumpstart-foundation-models/question_answering_retrieval_augmented_generation/question_answering_langchain_jumpstart.html)
+ [Retrieval-Augmented Generation: Question Answering based on Custom Dataset](https://sagemaker-examples.readthedocs.io/en/latest/introduction_to_amazon_algorithms/jumpstart-foundation-models/question_answering_retrieval_augmented_generation/question_answering_jumpstart_knn.html)
+ [Retrieval-Augmented Generation: Question Answering using Llama-2 and Text Embedding Models](https://sagemaker-examples.readthedocs.io/en/latest/introduction_to_amazon_algorithms/jumpstart-foundation-models/question_answering_retrieval_augmented_generation/question_answering_text_embedding_llama-2_jumpstart.html)
+ [Amazon SageMaker JumpStart - Text Embedding and Sentence Similarity](https://sagemaker-examples.readthedocs.io/en/latest/introduction_to_amazon_algorithms/jumpstart-foundation-models/question_answering_retrieval_augmented_generation/text-embedding-sentence-similarity.html)