Remove 2023 Remove Accountability Remove Scripts
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Efficiently fine-tune the ESM-2 protein language model with Amazon SageMaker

AWS Machine Learning

Nature Reviews Drug Discovery 22, 260–260 (2023). For example, in 2023, a research team described training a 100 billion-parameter pLM on 768 A100 GPUs for 164 days! In the following sections, we go through the steps to prepare your training data, create a training script, and run a SageMaker training job.

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Overcoming common contact center challenges with generative AI and Amazon SageMaker Canvas

AWS Machine Learning

In October 2023, SageMaker Canvas announced support for foundation models among its ready-to-use models , powered by Amazon Bedrock and Amazon SageMaker JumpStart. Typically, call scripts guide agents through calls and outline addressing issues.

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Open source observability for AWS Inferentia nodes within Amazon EKS clusters

AWS Machine Learning

companion script (both commands are part of the container): neuron-monitor | neuron-monitor-prometheus.py --port The command uses the following components: neuron-monitor collects metrics and stats from the Neuron applications running on the system and streams the collected data to stdout in JSON format neuron-monitor-prometheus.py

APIs 116
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Generating fashion product descriptions by fine-tuning a vision-language model with SageMaker and Amazon Bedrock

AWS Machine Learning

For details, see Creating an AWS account. Ensure sufficient capacity for this instance in your AWS account by requesting a quota increase if required. The script also merges the LoRA weights into the model weights after training. We use Amazon SageMaker Studio with the ml.t3.medium medium instance and the Data Science 3.0

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Use Amazon SageMaker Studio to build a RAG question answering solution with Llama 2, LangChain, and Pinecone for fast experimentation

AWS Machine Learning

Prerequisites To follow the steps in this post, you need to have an AWS account and an AWS Identity and Access Management (IAM) role with permissions to create and access the solution resources. If you are new to AWS, see Create a standalone AWS account. You need to have an account with Pinecone to use it as a vector database.

APIs 116
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Scaling Large Language Model (LLM) training with Amazon EC2 Trn1 UltraClusters

AWS Machine Learning

Briefly, this is made possible by an installation script specified by CustomActions in the YAML file used for creating the ParallelCluster (see Create ParallelCluster ). You can invoke neuron-top during the training script run to inspect NeuronCore utilization at each node. Complete instructions can be found on GitHub.

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Best UX/UI Cybersecurity Tips for 2023

Nicereply

Read the best UX/UI cybersecurity tips and tricks for 2023. This eliminates the need for users to remember multiple usernames and passwords and reduces the risk of unauthorized access to user accounts. They help protect user data, prevent unauthorized access , and provide enhanced security for user accounts.