![]() ![]() ![]() \"We\'re excited to offer Cohere\'s general purpose large language model with Amazon SageMaker. The Medium model is deployed in containers that enable low-latency inference on a diverse set of hardware accelerators available on AWS, providing different cost and performance advantages for SageMaker customers.\n\n\"Amazon SageMaker provides the broadest and most comprehensive set of services that eliminate heavy lifting from each step of the machine learning process,\" said Rajneesh Singh, General Manager AI/ML at Amazon Web Services. The Medium generation model excels at tasks that require fast responses, such as question answering, copywriting, or paraphrasing. Companies can use the models out of the box or tailor them to their particular needs using their own custom data.\n\nDevelopers using SageMaker will have access to Cohere\'s Medium generation language model. The company builds and continually improves its general-purpose large language models (LLMs), making them accessible via a simple-to-use platform. Cohere helps developers and businesses automate a wide range of tasks, such as copywriting, named entity recognition, paraphrasing, text summarization, and classification. The company\'s mission is to enable developers and businesses to add language AI to their technology stack and build game-changing applications with it. Developers, data scientists, and business analysts use Amazon SageMaker to build, train, and deploy ML models quickly and easily using its fully managed infrastructure, tools, and workflows.\n\nAt Cohere, the focus is on language. This makes it easier for developers to deploy Cohere\'s pre-trained generation language model to Amazon SageMaker, an end-to-end machine learning (ML) service. Cohere\'s state-of-the-art language AI is now available through Amazon SageMaker. 4 text= 'It\'s an exciting day for the development community. ![]()
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