# Task-Specific Models
<a name="jumpstart-models"></a>

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 AI Automatic Model Tuning](https://docs.amazonaws.cn/sagemaker/latest/dg/automatic-model-tuning.html).​ 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](https://sagemaker.readthedocs.io/en/stable/overview.html#use-prebuilt-models-with-sagemaker-jumpstart). For a list of all available models, see the [JumpStart Available Model Table](https://sagemaker.readthedocs.io/en/v2.132.0/doc_utils/pretrainedmodels.html).

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](https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_image_classification/Amazon_JumpStart_Image_Classification.ipynb)  | 
| Object detection  | Yes  | Yes  | PyTorch, TensorFlow, MXNet |  [Introduction to JumpStart - Object Detection](https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_object_detection/Amazon_JumpStart_Object_Detection.ipynb)  | 
| Semantic segmentation  | Yes  | Yes  | MXNet  |  [Introduction to JumpStart - Semantic Segmentation](https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_semantic_segmentation/Amazon_JumpStart_Semantic_Segmentation.ipynb)  | 
| Instance segmentation  | Yes  | Yes  | MXNet  |  [Introduction to JumpStart - Instance Segmentation](https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_instance_segmentation/Amazon_JumpStart_Instance_Segmentation.ipynb)  | 
| Image embedding  | Yes  | No  | TensorFlow, MXNet |  [Introduction to JumpStart - Image Embedding](https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_image_embedding/Amazon_JumpStart_Image_Embedding.ipynb)  | 
| Text classification  | Yes  | Yes  | TensorFlow |  [Introduction to JumpStart - Text Classification](https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_text_classification/Amazon_JumpStart_Text_Classification.ipynb)  | 
| Sentence pair classification  | Yes  | Yes  | TensorFlow, Hugging Face |  [Introduction to JumpStart - Sentence Pair Classification](https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_sentence_pair_classification/Amazon_JumpStart_Sentence_Pair_Classification.ipynb)  | 
| Question answering  | Yes  | Yes  | PyTorch, Hugging Face |  [Introduction to JumpStart – Question Answering](https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_question_answering/Amazon_JumpStart_Question_Answering.ipynb)  | 
| Named entity recognition  | Yes  | No  | Hugging Face  |  [Introduction to JumpStart - Named Entity Recognition](https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_named_entity_recognition/Amazon_JumpStart_Named_Entity_Recognition.ipynb)  | 
| Text summarization  | Yes  | No  | Hugging Face  |  [Introduction to JumpStart - Text Summarization](https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_text_summarization/Amazon_JumpStart_Text_Summarization.ipynb)  | 
| Text generation  | Yes  | No  | Hugging Face  |  [Introduction to JumpStart - Text Generation](https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_text_generation/Amazon_JumpStart_Text_Generation.ipynb)  | 
| Machine translation  | Yes  | No  | Hugging Face  |  [Introduction to JumpStart - Machine Translation](https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_machine_translation/Amazon_JumpStart_Machine_Translation.ipynb)  | 
| Text embedding  | Yes  | No  | TensorFlow, MXNet |  [Introduction to JumpStart - Text Embedding](https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_text_embedding/Amazon_JumpStart_Text_Embedding.ipynb)  | 
| Tabular classification  | Yes  | Yes  | LightGBM, CatBoost, XGBoost, AutoGluon-Tabular, TabTransformer, Linear Learner |  [Introduction to JumpStart - Tabular Classification - LightGBM, CatBoost](https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/lightgbm_catboost_tabular/Amazon_Tabular_Classification_LightGBM_CatBoost.ipynb) [Introduction to JumpStart - Tabular Classification - XGBoost, Linear Learner](https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/xgboost_linear_learner_tabular/Amazon_Tabular_Classification_XGBoost_LinearLearner.ipynb) [Introduction to JumpStart - Tabular Classification - AutoGluon Learner](https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/autogluon_tabular/Amazon_Tabular_Classification_AutoGluon.ipynb) [Introduction to JumpStart - Tabular Classification - TabTransformer Learner](https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/tabtransformer_tabular/Amazon_Tabular_Classification_TabTransformer.ipynb)  | 
| Tabular regression  | Yes  | Yes  | LightGBM, CatBoost, XGBoost, AutoGluon-Tabular, TabTransformer, Linear Learner |  [Introduction to JumpStart - Tabular Regression - LightGBM, CatBoost](https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/lightgbm_catboost_tabular/Amazon_Tabular_Regression_LightGBM_CatBoost.ipynb) [Introduction to JumpStart – Tabular Regression - XGBoost, Linear Learner](https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/xgboost_linear_learner_tabular/Amazon_Tabular_Regression_XGBoost_LinearLearner.ipynb) [Introduction to JumpStart – Tabular Regression - AutoGluon Learner](https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/autogluon_tabular/Amazon_Tabular_Regression_AutoGluon.ipynb) [Introduction to JumpStart – Tabular Regression - TabTransformer Learner](https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/tabtransformer_tabular/Amazon_Tabular_Regression_TabTransformer.ipynb)  |