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Benchmarking Amazon Nova and GPT-4o models with FloTorch

AWS Machine Learning

Using its enterprise software, FloTorch conducted an extensive comparison between Amazon Nova models and OpenAIs GPT-4o models with the Comprehensive Retrieval Augmented Generation (CRAG) benchmark dataset. simple Finance Did meta have any mergers or acquisitions in 2022? simple_w_condition Open Can i make cookies in an air fryer?

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Improve price performance of your model training using Amazon SageMaker heterogeneous clusters

AWS Machine Learning

To address this issue, in July 2022, we launched heterogeneous clusters for Amazon SageMaker model training, which enables you to launch training jobs that use different instance types in a single job. Performance benchmark results. In this post, we discuss the following topics: How heterogeneous clusters help remove CPU bottlenecks.

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Best practices for load testing Amazon SageMaker real-time inference endpoints

AWS Machine Learning

We first benchmark the performance of our model on a single instance to identify the TPS it can handle per our acceptable latency requirements. Note that the model container also includes any custom inference code or scripts that you have passed for inference. Any issues related to end-to-end latency can then be isolated separately.

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How Games24x7 transformed their retraining MLOps pipelines with Amazon SageMaker

AWS Machine Learning

The code to invoke the pipeline script is available in the Studio notebooks, and we can change the hyperparameters and input/output when invoking the pipeline. This is quite different from our earlier method where we had all the parameters hard coded within the scripts and all the processes were inextricably linked.

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New performance improvements in Amazon SageMaker model parallel library

AWS Machine Learning

You can learn more about Stability AI’s mission and partnership with AWS in the talk of Stability AI CEO at AWS re:Invent 2022 or in this blog post. Finally, we’ll benchmark performance of 13B, 50B, and 100B parameter auto-regressive models and wrap up with future work. Benchmarking performance. 13B parameter GPT-NeoX.

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Scaling distributed training with AWS Trainium and Amazon EKS

AWS Machine Learning

In late 2022, AWS announced the general availability of Amazon EC2 Trn1 instances powered by AWS Trainium —a purpose-built machine learning (ML) accelerator optimized to provide a high-performance, cost-effective, and massively scalable platform for training deep learning models in the cloud.

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Scaling Large Language Model (LLM) training with Amazon EC2 Trn1 UltraClusters

AWS Machine Learning

In October 2022, we launched Amazon EC2 Trn1 Instances , powered by AWS Trainium , which is the second generation machine learning accelerator designed by AWS. Briefly, this is made possible by an installation script specified by CustomActions in the YAML file used for creating the ParallelCluster (see Create ParallelCluster ).

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