SageMaker JumpStart models also improve security posture with endpoints that enable network isolation. The OpenAI Whisper model uses the huggingface-pytorch-inference container. As a SageMaker JumpStart model hub customer, you can use ASR without having to maintain the model script outside of the SageMaker SDK. In this post, we show you how to deploy the OpenAI Whisper model and invoke the model to transcribe and translate audio. You can also do ASR using Amazon Transcribe ,a fully-managed and continuously trained automatic speech recognition service. Sagemaker JumpStart is the machine learning (ML) hub of SageMaker that provides access to foundation models in addition to built-in algorithms and end-to-end solution templates to help you quickly get started with ML. Trained on 680 thousand hours of labelled data, Whisper models demonstrate a strong ability to generalize to many datasets and domains without the need for fine-tuning. Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation. Today, we’re excited to announce that the OpenAI Whisper foundation model is available for customers using Amazon SageMaker JumpStart.
