AWS Machine Learning Blog

DECEMBER 12, 2023

Walkthrough Download the pre-tokenized Wikipedia dataset as shown: export DATA_DIR=~/examples_datasets/gpt2 mkdir -p ${DATA_DIR} && cd ${DATA_DIR} wget [link] wget [link] aws s3 cp s3://neuron-s3/training_datasets/gpt/wikipedia/my-gpt2_text_document.bin. Each trn1.32xl has 16 accelerators with two workers per accelerator.

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AWS Machine Learning Blog

APRIL 29, 2024

Besides easy access, using Trainium with Metaflow brings a few additional benefits: Infrastructure accessibility Metaflow is known for its developer-friendly APIs that allow ML/AI developers to focus on developing models and applications, and not worry about infrastructure. Complete the following steps: Download the CloudFormation template.

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Hacker News

JULY 18, 2023

What if you could automatically shard your PostgreSQL database across any number of servers and get industry-leading performance at scale without any special data modelling steps? Schema-based sharding has almost no data modelling restrictions or special steps compared to unsharded PostgreSQL.

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AWS Machine Learning Blog

APRIL 25, 2024

We provide a comprehensive guide on how to deploy speaker segmentation and clustering solutions using SageMaker on the AWS Cloud. Create a model function for accessing PyAnnote speaker diarization from Hugging Face You can use the Hugging Face Hub to access the desired pre-trained PyAnnote speaker diarization model.

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AWS Machine Learning Blog

SEPTEMBER 19, 2024

You could further optimize the time for training in the following graph by using a SageMaker managed warm pool and accessing pre-downloaded models using Amazon Elastic File System (Amazon EFS). Challenges with fine-tuning LLMs Generative AI models offer many promising business use cases. 8b-lora.yaml on an ml.p4d.24xlarge

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AWS Machine Learning Blog

NOVEMBER 15, 2023

An AutoML tool applies a combination of different algorithms and various preprocessing techniques to your data. For example, it can scale the data, perform univariate feature selection, conduct PCA at different variance threshold levels, and apply clustering.

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Pickl AI

OCTOBER 16, 2024

Scalability : TensorFlow can scale across multiple machines and run on various hardware platforms, from mobile devices to high-performance clusters. Flexibility : It allows easy model building with high-level APIs like Keras while providing low-level control for custom operations. Ensure Python is installed: It works with Python 3.7

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