Task-Specific Models - Amazon SageMaker
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Task-Specific Models

JumpStart supports task-specific models across fifteen of the most popular problem types. Of the supported problem types, Vision and NLP-related types total thirteen. There are eight problem types that support incremental training and fine-tuning. For more information about incremental training and hyper-parameter tuning, see SageMaker Automatic Model Tuning.​ JumpStart also supports four popular algorithms for tabular data modeling.

You can search and browse models from the JumpStart landing page in Studio or Studio Classic. When you select a model, the model detail page provides information about the model, and you can train and deploy your model in a few steps. The description section describes what you can do with the model, the expected types of inputs and outputs, and the data type needed for fine-tuning your model.

You can also programmatically utilize models with the SageMaker Python SDK. For a list of all available models, see the JumpStart Available Model Table.

The list of problem types and links to their example Jupyter notebooks are summarized in the following table.

Problem types Supports inference with pre-trained models Trainable on a custom dataset Supported frameworks Example Notebooks
Image classification Yes Yes

PyTorch, TensorFlow

Introduction to JumpStart - Image Classification
Object detection Yes Yes PyTorch, TensorFlow, MXNet

Introduction to JumpStart - Object Detection
Semantic segmentation Yes Yes MXNet

Introduction to JumpStart - Semantic Segmentation
Instance segmentation Yes Yes MXNet

Introduction to JumpStart - Instance Segmentation
Image embedding Yes No TensorFlow, MXNet

Introduction to JumpStart - Image Embedding
Text classification Yes Yes TensorFlow

Introduction to JumpStart - Text Classification
Sentence pair classification Yes Yes TensorFlow, Hugging Face

Introduction to JumpStart - Sentence Pair Classification
Question answering Yes Yes PyTorch, Hugging Face

Introduction to JumpStart – Question Answering
Named entity recognition Yes No Hugging Face

Introduction to JumpStart - Named Entity Recognition
Text summarization Yes No Hugging Face

Introduction to JumpStart - Text Summarization
Text generation Yes No Hugging Face

Introduction to JumpStart - Text Generation
Machine translation Yes No Hugging Face

Introduction to JumpStart - Machine Translation
Text embedding Yes No TensorFlow, MXNet

Introduction to JumpStart - Text Embedding
Tabular classification Yes Yes LightGBM, CatBoost, XGBoost, AutoGluon-Tabular, TabTransformer, Linear Learner

Introduction to JumpStart - Tabular Classification - LightGBM, CatBoost

Introduction to JumpStart - Tabular Classification - XGBoost, Linear Learner

Introduction to JumpStart - Tabular Classification - AutoGluon Learner

Introduction to JumpStart - Tabular Classification - TabTransformer Learner
Tabular regression Yes Yes LightGBM, CatBoost, XGBoost, AutoGluon-Tabular, TabTransformer, Linear Learner

Introduction to JumpStart - Tabular Regression - LightGBM, CatBoost

Introduction to JumpStart – Tabular Regression - XGBoost, Linear Learner

Introduction to JumpStart – Tabular Regression - AutoGluon Learner

Introduction to JumpStart – Tabular Regression - TabTransformer Learner