Today, we announce the public availability of Amazon’s state-of-the-art Alexa Teacher Model with 20 billion parameters  (AlexaTM 20B) through Amazon SageMaker JumpStart, SageMaker’s machine learning hub. AlexaTM 20B is a multilingual large-scale sequence-to-sequence (seq2seq) language model developed by Amazon. You can use AlexaTM 20B for a wide range of industry use-cases, from summarizing financial reports to question answering for customer service chatbots. It can be applied even when there are only a few available training examples, or even none at all. AlexaTM 20B outperforms a 175 billion GPT-3 model on zero-shot learning tasks such as SuperGLUE and shows state-of-the-art performance for multilingual zero-shot tasks such as XNLI.
In this post, we provide an overview of how to deploy and run inference with the AlexaTM 20B model programmatically through JumpStart APIs, available in the SageMaker Python SDK. We exemplify how you can use this model to translate between multiple languages, summarize

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