AWS Machine Learning Blog

JULY 1, 2024

The user prompt is augmented along with the results returned from the knowledge base as an additional context and sent to the LLM to generate a response. Create a knowledge base To create a new knowledge base in Amazon Bedrock, complete the following steps. You should see a Successfully built message when the build is complete.

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AWS Machine Learning Blog

AUGUST 22, 2024

The following figure shows the Discovery Navigator generative AI auto-summary pipeline. The generative AI large language model (LLM) can be prompted with questions or asked to summarize a given text. In that role, she completed and obtained CMS approval of hundreds of Medicare Set Asides.

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AWS Machine Learning Blog

OCTOBER 11, 2023

The LMI container has a powerful serving stack called DJL serving that is agnostic to the underlying LLM. It provides system-level configuration parameters that can be tuned for extracting the best performance of the hosting infrastructure for a given LLM. These cached key and value tensors are often referred to as the KV cache.

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AWS Machine Learning Blog

JUNE 13, 2023

Last week, Technology Innovation Institute (TII) launched TII Falcon LLM , an open-source foundational large language model (LLM). The result of this effort is TII Falcon LLM. SageMaker large model inference DLCs simplify LLM hosting Hosting LLMs such as Falcon-40B and Falcon-7B can be challenging.

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AWS Machine Learning Blog

NOVEMBER 15, 2024

The integration of these multimodal capabilities has unlocked new possibilities for businesses and individuals, revolutionizing fields such as content creation, visual analytics, and software development. In the metadata.jsonl file, each example is a dictionary that contains three keys named file_name , prompt , and completion.

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AWS Machine Learning Blog

DECEMBER 13, 2023

We use the AWS Neuron software development kit (SDK) to access the AWS Inferentia2 device and benefit from its high performance. This compiles and serve an LLM on an Inf2 instance. The complete code samples with instructions can be found in this GitHub repository.

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AWS Machine Learning Blog

NOVEMBER 15, 2023

Llama 2 stands at the forefront of AI innovation, embodying an advanced auto-regressive language model developed on a sophisticated transformer foundation. In this post, we explore best practices for prompting the Llama 2 Chat LLM. The complete example is shown in the accompanying notebook.

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AWS Machine Learning Blog

AUGUST 5, 2024

This technique improves LLM inference throughput and output token latency (TPOT). Next, we perform auto-regressive token generation where the output tokens are generated sequentially. This means we will be repeating this process more times to complete the response, resulting in slower overall processing.

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Unite.AI

AUGUST 1, 2023

GPT-4: Prompt Engineering ChatGPT has transformed the chatbot landscape, offering human-like responses to user inputs and expanding its applications across domains – from software development and testing to business communication, and even the creation of poetry. This demonstrates a classic case of ‘knowledge conflict'.

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AWS Machine Learning Blog

NOVEMBER 30, 2023

Deploy a SageMaker model In the most basic scenario, all you need to do is select a deployable model from the Models page or an LLM from the SageMaker JumpStart page, select an instance type, set the initial instance count, and deploy the model. You can also edit the auto scaling policy on the Auto-scaling tab on this page.

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AWS Machine Learning Blog

MAY 31, 2023

Complete the following steps: Launch the provided CloudFormation template. When the stack is complete, you can move to the next step. Complete the following steps: On the Amazon ECR console, create a new repository. To do a complete cleanup, delete the CloudFormation stack to remove all resources created by this template.

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AWS Machine Learning Blog

MAY 4, 2023

For ultra-large models that don’t fit into a single accelerator, data flows directly between accelerators with NeuronLink, bypassing the CPU completely. These endpoints are fully managed and support auto scaling. xlarge" ) Refer to Developer Flows for more details on typical development flows of Inf2 on SageMaker with sample scripts.

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Unite.AI

APRIL 18, 2024

From self-driving cars to language models that can engage in human-like conversations, AI is rapidly transforming various industries, and software development is no exception. This remarkable tool leverages state-of-the-art language models like GPT-4, streamlining the development cycle and enhancing developer productivity.

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Unite.AI

MAY 28, 2024

Before MonsterAPI, he ran two startups, including one that developed a wearable safety device for women in India, in collaboration with the Government of India and IIT Delhi. Our Mission has always been “to help software developers fine-tune and deploy AI models faster and in the easiest manner possible.”

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AWS Machine Learning Blog

JUNE 5, 2023

Today, as part of Amazon Web Services’ partnership with Hugging Face, we are excited to announce the release of a new Hugging Face Deep Learning Container (DLC) for inference with Large Language Models (LLMs). Hosting LLMs at scale presents a unique set of complex engineering challenges. You can find our complete example notebook here.

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AWS Machine Learning Blog

JULY 23, 2024

collection of multilingual large language models (LLMs), which includes pre-trained and instruction tuned generative AI models in 8B, 70B, and 405B sizes, is available through Amazon SageMaker JumpStart to deploy for inference. is an auto-regressive language model that uses an optimized transformer architecture. The Llama 3.1

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Flipboard

APRIL 13, 2023

For instance, a financial firm that needs to auto-generate a daily activity report for internal circulation using all the relevant transactions can customize the model with proprietary data, which will include past reports, so that the FM learns how these reports should read and what data was used to generate them.

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