AWS Machine Learning

JUNE 15, 2023

It features interactive Jupyter notebooks with self-contained code in PyTorch, JAX, TensorFlow, and MXNet, as well as real-world examples, exposition figures, and math. ACT allows you to customize translation output on the fly by providing tailored translation examples in the form of parallel data.

APIs 79

APIs Benchmark Best practices Engineering 79

AWS Machine Learning

NOVEMBER 22, 2023

You can save time, money, and labor by implementing classifications in your workflow, and documents go to downstream applications and APIs based on document type. For example, by storing a document in the different processed phases, you can reverse processing to the previous step if needed.

APIs 98

APIs Metrics Enterprise Benchmark 98

AWS Machine Learning

JANUARY 29, 2024

This post explores these relationships via a comprehensive benchmarking of LLMs available in Amazon SageMaker JumpStart, including Llama 2, Falcon, and Mistral variants. We provide theoretical principles on how accelerator specifications impact LLM benchmarking. Additionally, models are fully sharded on the supported instance.

Benchmark 100

Benchmark APIs Enterprise Accountability 100

AWS Machine Learning

MARCH 13, 2024

You will also find a Deploy button, which takes you to a landing page where you can test inference with an example payload. Deploy Gemma with SageMaker Python SDK You can find the code showing the deployment of Gemma on JumpStart and an example of how to use the deployed model in this GitHub notebook. This looks pretty good!

Benchmark 112

Benchmark Scripts APIs Feedback 112

AWS Machine Learning

MAY 17, 2024

What is Mixtral 8x22B Mixtral 8x22B is Mistral AI’s latest open-weights model and sets a new standard for performance and efficiency of available foundation models , as measured by Mistral AI across standard industry benchmarks. In this section, we provide example prompts. Deploy a model Deployment starts when you choose Deploy.

APIs 106

APIs Benchmark Personalization Enterprise 106

AWS Machine Learning

MARCH 14, 2024

By the end, you will have solid guidelines and a helpful flow chart for determining the best method to develop your own FM-powered applications, grounded in real-life examples. The following screenshot shows an example of a zero-shot prompt with the Anthropic Claude 2.1 In these instructions, we didn’t provide any examples.

Best practices 110

Best practices Engineering Chatbots Enterprise 110

AWS Machine Learning

FEBRUARY 6, 2023

The former question addresses model selection across model architectures, while the latter question concerns benchmarking trained models against a test dataset. This post provides details on how to implement large-scale Amazon SageMaker benchmarking and model selection tasks. swin-large-patch4-window7-224 195.4M efficientnet-b5 29.0M

APIs 75

APIs Scripts Metrics Benchmark 75