A great detailed overview of Llama2 on Inferentia 2, including performance metrics and code samples on getting started. Startup up an Inf2 instance and give it a try today on EC2 or Sagemaker. #aws #generativeai #inf2 #machinelearning https://lnkd.in/ecjpV38b
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Deploying Llama2 models can be expensive but AWS has specific hardware in the Inferential family that supports cost effective deployment. The blog post discusses the deployment of Llama 2 on Amazon EC2 Inf2 instances using AWS Inferentia2 for both training and inference. It provides detailed steps on creating, compiling, and deploying the Llama-2 model using the latest AWS Neuron SDK release, achieving high performance at low cost. https://lnkd.in/gDib5znW
PyTorch
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Check out this awesome blogpost from my colleagues Jianying Lang, Fei Chen et.al. on training SOTA LLMs on AWS Trainium, our AWS ML chips.
Excellent work by our WWSO Advanced Computing and Service teams in scaling training workloads on Trainium. https://lnkd.in/gje7QHKg #hpc #genai #AWS
End-to-end LLM training on instance clusters with over 100 nodes using AWS Trainium | Amazon Web Services
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🚨 NEW BLOG ALERT 🚨 Learn how to perform continued pre-training of #Llama models using Pipeline Parallelism and Tensor Parallelism on #SageMaker with AWS #Trainium instances. With up to 50% cost-to-train savings over comparable training optimized EC2 instances, this blog is a must-read for anyone interested in #MachineLearning and #DeepLearning. Check out the link below to learn more! Link: https://lnkd.in/gi4pDUQz #AWS #SageMaker #NeuronDistributedLibrary #PipelineParallelism #TensorParallelism
Simple guide to training Llama 2 with AWS Trainium on Amazon SageMaker | Amazon Web Services
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This post shows how to accelerate pre-training of large language models by scaling up to 128 trn1.32xlarge nodes, using a 2-7B Llama model as an example. It shares best practices for efficient, stable training of LLMs on AWS Trainium with 100+ nodes, and recovering from failures. #aws #awscloud #cloud #amazonec2 #awsneuron #awstrainium #bestpractices #technicalhowto #distributedtraining #neuron
End-to-end LLM training on instance clusters with over 100 nodes using AWS Trainium
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Google Developer Expert (GDE), AWS Community Builder, Senior Manager Data Science, Consultant, Trainer, Podcaster, Founder Malaysia R User Group, AI & ML Malaysia User Group
AWS Step Functions is a serverless function orchestrator that makes it easy to sequence AWS Lambda functions and multiple AWS services into business-critical applications with Amazon Bedrock #aws #amazonbedrock #awsstepfunctions https://lnkd.in/dNWyVvSg
Build generative AI apps using AWS Step Functions and Amazon Bedrock | Amazon Web Services
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Data Enthusiast | Data Analyst | Data Science | ML/DL/AI | Analytics | Visualization | ETL | UI/UX | NFT | Power Apps | IT | Content Writer | Jobs/Recruitment | Quoran | Follow for more
"Learn how to trace EC2 console activity in multiple code formats using AWS Console-to-Code. With this generative AI capability, you can easily convert console actions into reusable code in your preferred language. Check out the detailed overview and takeaway in the post. #AWS #AI #ML #CloudComputing #TechNews"
"Learn how to trace EC2 console activity in multiple code formats using AWS Console-to-Code. With this generative AI capability, you can easily convert console actions into reusable code in your preferred language. Check out the detailed overview and takeaway in the post. #AWS #AI #ML #CloudComputing #TechNews"
dev.to
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One more step toward cheaper or faster LLM inference on AWS? Also what about Neuron support on Lambda and ECS Fargate? (cold start is an issue .. I know) https://lnkd.in/gyZgY-53
AWS Neuron introduces speculative decoding and vLLM support
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In a few clicks from SageMaker JumpStart, you can now deploy the 132B parameter DBRX model trained by Databricks, with its efficient 36B active parameters, it establishes new benchmarks for open-source LLM performance, speed and training efficiency. It outperforms models like GPT-3.5 and Llama 2 while remaining accessible for customization by enterprises. Read our blog: https://lnkd.in/g4An6Vb3 #generativeAI #LLM #AWS #machinelearning #AI #cloud Armando DiazShikhar KwatraNiithiyn Vijeaswaran
Databricks DBRX is now available in Amazon SageMaker JumpStart | Amazon Web Services
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https://lnkd.in/grJhud4b Fanghua (Joshua) Yu presents a simple yet effective method to enhance similarity search in #GenAI solutions like #RAG, using #Neo4j APOC #ML procedures, and compares results across major cloud providers without relying on conventional techniques like model fine-tuning or prompt engineering. He includes examples and test results using embeddings from #Azure #OpenAI, #Google #VertexAI, and #AWS #Bedrock #graphdatabases #generatieveai #llms #largelanguagemodels
An Extremely Simple but Effective Way to Improve Search over Text Embeddings
medium.com
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Explore AWS's approach of fine-tuning the powerful Llama 2 model using QLoRA and deploying it on Amazon SageMaker, supercharged by the new AWS EC2 Inferentia2 instances. This approach not only enhances model performance but also ensures cost-efficient, high-speed ML inference, marking significant improvements in your AI applications. #finetuning #inf2 #QLoRA #SageMaker https://lnkd.in/eK5Vmuyx
Fine-tune Llama 2 using QLoRA and Deploy it on Amazon SageMaker with AWS Inferentia2 | Amazon Web Services
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