Smart Data Collective

AUGUST 5, 2021

In this blog, we will cover an overview of Delta Lakes , its advantages, and how the above challenges can be overcome by moving to Delta Lake and migrating to Spark 3.0 The transaction log allows various users to read and write to the given table in parallel. from Spark 2.4. . Advantages of using Delta Lakes.

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AWS Machine Learning Blog

NOVEMBER 1, 2023

Now a part of Reveal’s AI-powered eDiscovery platform, Logikcull is a self-service solution that allows legal professionals to process, review, tag, and produce electronic documents as part of a lawsuit or investigation. Logikcull uses this confidence score to assign the tag PII Detected to the documents.

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AWS Machine Learning Blog

APRIL 4, 2024

The following figure shows an example of our tagging system. With SageMaker MMEs, we can run batches of 12 images in parallel, and the full batch completes in less than 2 seconds. For example, we identify if the brand is on a banner or a shirt. To understand our scaling and cost challenges, let’s look at some representative numbers.

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PyImageSearch

MAY 22, 2023

Transformers and Parallel Decoding for Object Detection ⚡ A Niche Solution ? Object Detection from the Old Days (problem statement) Set Prediction for Object Detection (methodology 1) Transformers and Parallel Decoding for Object Detection (methodology 2) A Simple Solution (solution) Object Detection from the Old Days ? Quiz Time! ?

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PyImageSearch

JUNE 26, 2023

End-to-End Trainability ⏩ Parallel Decoding for Enhanced Efficiency ❌ Elimination of Hand-Crafted Features ? In the first blog post of this series, we understood why and how DETR was born, its key features, and how it differs from previous models. Connect with us on Twitter by tagging @pyimagesearch. CNN Backbone ?

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AWS Machine Learning Blog

NOVEMBER 30, 2023

It also provides a framework for running parallel jobs using the NVIDIA Collective Communications Library (NCCL) or Message Passing Interface (MPI) standards. Provider a cluster name and optionally any tags to apply to cluster resources, then choose Next. Choose Create a cluster.

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AWS Machine Learning Blog

MAY 30, 2023

You can also apply additional filters such as account number, Amazon Elastic Compute Cloud (Amazon EC2) instance type, cost allocation tag, Region, and more. You can also include cost-allocation tags in your query for an additional level of granularity. You can build custom queries to look up AWS CUR data using standard SQL.

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Hacker News

MARCH 25, 2022

In addition, the math that transformers use lends itself to parallel processing, so these models can run fast. Transformers use positional encoders to tag data elements coming in and out of the network. Attention units follow these tags, calculating a kind of algebraic map of how each element relates to the others.

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Mlearning.ai

FEBRUARY 6, 2023

Use SageMaker Processing Jobs to easily run inference on your large Dataset with Hugging Face’s Transformer Models Photo by Alex Kulikov on Unsplash This blog will give you a complete walk through of running a distributed batch inference on large data in production. We’ll be using Amazon Sagemaker, a fully managed machine learning service.

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Hacker News

DECEMBER 3, 2023

The very next day I published a blog post about how I made it so fast to search through 154M records and thus began a now 185-post epic where I began detailing the minutiae of how I built this thing, the decisions I made about how to run it and commentary on all sorts of different breaches. And then ensured could never happen again.

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AWS Machine Learning Blog

JULY 5, 2023

The HTML audio tag is used for this purpose). The state machine can invoke the parallel branch condition to invoke two different Lambda functions: one to generate speech and another to generate speech marks. In this post, we present an interesting approach for highlighting text as it’s being spoken using Amazon Polly.

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AWS Machine Learning Blog

MAY 25, 2023

Figure 2: Service Quota Increase Request Use AWS Cloud Formation to create the solution stack We use AWS CloudFormation to create a SageMaker notebook called aws-llm-apps-blog and an IAM role called LLMAppsBlogIAMRole. Select the notebook aws-llm-apps-blog and choose Open JupyterLab.

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Flipboard

OCTOBER 9, 2023

In today’s blog, we will look at how we can create and build our own containers with a Dockerfile , followed by the most commonly used Docker commands and the concepts behind them. The container will have a parallel file structure from the local device, meaning we must copy the files to access them within the container.

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AssemblyAI

SEPTEMBER 22, 2023

In this blog post, we will break down the key ideas behind the latest approaches to AI music generation and outline the main differences in the current state-of-the-art models like MusicLM, MusicGen and StableAudio. ” But how do these new models for music generation work? CLAP is a more recent (and fully open-source) model.

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Google Research AI blog

DECEMBER 7, 2022

A Protocol for Evaluating the Faithfulness of Input Salience Methods for Text Classification (see blog post ) Jasmijn Bastings , Sebastian Ebert , Polina Zablotskaia , Anders Sandholm , Katja Filippova Intriguing Properties of Compression on Multilingual Models Kelechi Ogueji*, Orevaoghene Ahia, Gbemileke A.

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phData

DECEMBER 11, 2023

This blog serves as a helpful starting point to explore the best practices for utilizing Astronomer Cosmos to gain better observability and streamline your dbt workflows. This blog will demonstrate how we utilized the Cosmos DbtTaskGroup object to execute dbt snapshots, models, and other dbt commands in Airflow.

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Mlearning.ai

APRIL 1, 2023

In this blog post, we will discuss three popular word embedding techniques, namely Word2Vec , Doc2Vec , and Top2Vec. We then create a list of TaggedDocument objects with each sentence and a unique tag. The worker's parameter is set to 8 to parallelize the computation and speed up the training process.

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Mlearning.ai

DECEMBER 21, 2023

While the weaknesses of LLMs were being discussed, a parallel discourse around providing context to the models started. Examples include removing HTML tags or eliminating specific elements that contribute noise, particularly when data is sourced from the web. In essence, it meant creating a ChatGPT on proprietary data.

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Heartbeat

NOVEMBER 6, 2023

Depending on your local system, you should run tasks in sequence or parallel if you have a high-end computer and your pipeline configuration. Sequential Execution (Image by Author) Use the other types of executors if you need to run tasks in parallel. You can choose to tag the photo with any name of your choice.

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AWS Machine Learning Blog

JANUARY 17, 2023

We set the total number of tuning jobs as 10 and distribute these jobs on five different Amazon Elastic Compute Cloud (Amazon EC2) instances for running parallel tuning jobs. /containers/huggingface_transformer_randomforest').resolve()), containers/huggingface_transformer_randomforest').resolve()), containers/autogluon_multimodal_ensemble').resolve()),

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AWS Machine Learning Blog

MAY 30, 2023

You can also apply additional filters such as account number, EC2 instance type, cost allocation tag, Region, and more. You can also include cost-allocation tags in your query for an additional level of granularity. The following screenshot shows cost and usage graphs for the selected hosting usage types.

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AWS Machine Learning Blog

APRIL 7, 2023

To learn more, you can visit this guide on the AWS Containers Blog or Verizon’s 5GEdgeTutorials repository for one such example. In parallel, create an Identity Access Management (IAM) that provides Amazon EC2 instances access to read objects within the bucket. To do so, deploy an Amazon EKS cluster with an AWS Wavelength node group.

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AWS Machine Learning Blog

APRIL 25, 2023

In this release, you can run your local machine learning (ML) Python code as a single-node Amazon SageMaker training job or multiple parallel jobs. Infrastructure settings cover the network configuration, IAM roles, Amazon Simple Storage Service (Amazon S3) folder for input, output data, and tags. You only need to set it up one time.

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AWS Machine Learning Blog

NOVEMBER 1, 2023

It enables high-performance text generation using tensor parallelism, model parallelism, and dynamic batching supporting some leading open-source LLMs such as Falcon and Llama V2, as well as VLMs like IDEFICS. amazonaws.com # Build the TGI docker image locally docker build. -f

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Mlearning.ai

MARCH 2, 2023

This blog post promises to be easier to understand than the underlying research paper, especially for readers not that familiar with the field. Furthermore, due to a mostly high number of input tokens, the attention computation is usually parallelized in several so-called attention heads. References [1] Devlin, J., arXiv:1810.04805. [2]

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The MLOps Blog

JUNE 27, 2023

Comparing and visualizing experiments and models : what visualizations are supported, and does it have parallel coordinate plots? Distributed computing: Support distributed computing frameworks and technologies to leverage parallel processing, distributed training, or data partitioning for model training and inference.

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Explosion

AUGUST 1, 2019

Since this blog post was published, Hugging Face have released an updated and renamed transformers package that now supports both PyTorch and TensorFlow 2. We have updated our library and this blog post accordingly. The spacy-transformers package was previously called spacy-pytorch-transformers.

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Heartbeat

DECEMBER 27, 2023

Different VMs can be run on the same physical host; for example, a parallel physical host running Linux VM, macOS VM, and Microsoft VM. Next, let's proceed to build our Docker image using the tag (mutable reference name) shipping_app from this Dockerfile as follows: docker build -t shipping_app. CMD [“gunicorn”, “ — bind”, “0.0.0.0:5000”,wsgi:app”]:

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The MLOps Blog

OCTOBER 3, 2023

For example, Shopify published a blog post about Merlin. They just need to kind of tag things like “Hey, by the way, we’re using these data sources. What teams would do is build a parallel solution that was much better and then invite or onboard the data scientists to that path. We’re creating these features.

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