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Deploy DeepSeek-R1 Distilled Llama models in Amazon Bedrock

AWS Machine Learning Blog

Import the model Complete the following steps to import the model: On the Amazon Bedrock console, choose Imported models under Foundation models in the navigation pane. Importing the model will take several minutes depending on the model being imported (for example, the Distill-Llama-8B model could take 520 minutes to complete).

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HR and Talent in the Era of AI

IBM Journey to AI blog

In this new era, however, generative AI can deliver more using targeted advisors and the use cases that benefit from it will continue to expand. Processes such as job description creation, auto-grading video interviews and intelligent search that once required a human employee can now be completed using data-driven insights and generative AI.

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Deploy DeepSeek-R1 distilled Llama models with Amazon Bedrock Custom Model Import

AWS Machine Learning Blog

Import the model Complete the following steps to import the model: On the Amazon Bedrock console, choose Imported models under Foundation models in the navigation pane. Importing the model will take several minutes depending on the model being imported (for example, the Distill-Llama-8B model could take 520 minutes to complete).

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Advanced RAG patterns on Amazon SageMaker

AWS Machine Learning Blog

When you create an AWS account, you get a single sign-on (SSO) identity that has complete access to all the AWS services and resources in the account. Signing in to the AWS Management Console using the email address and password that you used to create the account gives you complete access to all the AWS resources in your account.

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16 Companies Leading the Way in AI and Data Science

ODSC - Open Data Science

Going from Data to Insights LexisNexis At HPCC Systems® from LexisNexis® Risk Solutions you’ll find “a consistent data-centric programming language, two processing platforms, and a single, complete end-to-end architecture for efficient processing.” These tools are designed to help companies derive insights from big data.

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Simple guide to training Llama 2 with AWS Trainium on Amazon SageMaker

AWS Machine Learning Blog

Llama 2 is an auto-regressive language model that uses an optimized transformer architecture and is intended for commercial and research use in English. This results in faster restarts and workload completion. Prerequisites You need to complete some prerequisites before you can run the first notebook.

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Get started quickly with AWS Trainium and AWS Inferentia using AWS Neuron DLAMI and AWS Neuron DLC

AWS Machine Learning Blog

Launch the instance using Neuron DLAMI Complete the following steps: On the Amazon EC2 console, choose your desired AWS Region and choose Launch Instance. You can update your Auto Scaling groups to use new AMI IDs without needing to create new launch templates or new versions of launch templates each time an AMI ID changes.