SageMaker JumpStart now provides TensorFlow Text Classification algorithms
Starting today, Amazon SageMaker JumpStart provides a new built-in algorithm for text classification: Text Classification - TensorFlow. It takes text as input and outputs probability for each of the class labels. It is a supervised learning algorithm that supports transfer learning for many pre-trained models available in TensorFlow Hub. These pre-trained models can be fine-tuned using transfer learning even when large amount of text are not available. It is available through the SageMaker built-in algorithms as well as through SageMaker JumpStart UI inside SageMaker Studio.
Starting today, Amazon SageMaker JumpStart provides a new built-in algorithm for text classification: Text Classification - TensorFlow. It takes text as input and outputs probability for each of the class labels. It is a supervised learning algorithm that supports transfer learning for many pre-trained models available in TensorFlow Hub. These pre-trained models can be fine-tuned using transfer learning even when large amount of text are not available. It is available through the SageMaker built-in algorithms as well as through SageMaker JumpStart UI inside SageMaker Studio.
This algorithm can be used in all regions where Amazon SageMaker JumpStart is available. To get started with these new models on SageMaker, refer to the documentation.
To learn how to use this algorithm, please see AWS documentation Text Classification - TensorFlow and the example notebook Introduction to JumpStart - Text Classification. More detailed explanation for how to use these algorithms can be found in the following blog on Transfer learning for TensorFlow text classification models in Amazon SageMaker.