PyImageSearch

SEPTEMBER 30, 2024

Home Table of Contents Introduction to GitHub Actions for Python Projects Introduction What Is CICD? For Python projects, CI/CD pipelines ensure that your code is consistently integrated and delivered with high quality and reliability. Git is the most commonly used VCS for Python projects, enabling collaboration and version tracking.

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Analytics Vidhya

APRIL 1, 2023

Introduction The current trend in NLP includes downloading and fine-tuning pre-trained models with millions or even billions of parameters. However, storing and sharing such large trained models is time-consuming, slow, and expensive.

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AWS Machine Learning Blog

DECEMBER 2, 2024

These improvements are available across a wide range of SageMaker’s Deep Learning Containers (DLCs), including Large Model Inference (LMI, powered by vLLM and multiple other frameworks), Hugging Face Text Generation Inference (TGI), PyTorch (Powered by TorchServe), and NVIDIA Triton.

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PyImageSearch

SEPTEMBER 23, 2024

Home Table of Contents Deploying a Vision Transformer Deep Learning Model with FastAPI in Python What Is FastAPI? You’ll learn how to structure your project for efficient model serving, implement robust testing strategies with PyTest, and manage dependencies to ensure a smooth deployment process. Testing main.py

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AWS Machine Learning Blog

DECEMBER 16, 2024

70B through SageMaker JumpStart offers two convenient approaches: using the intuitive SageMaker JumpStart UI or implementing programmatically through the SageMaker Python SDK. Lokeshwaran Ravi is a Senior Deep Learning Compiler Engineer at AWS, specializing in ML optimization, model acceleration, and AI security. Deploy Llama 3.3

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The MLOps Blog

MAY 10, 2023

How to save a trained model in Python? In this section, you will see different ways of saving machine learning (ML) as well as deep learning (DL) models. Saving trained model with pickle The pickle module can be used to serialize and deserialize the Python objects. Now let’s see how we can save our model.

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AWS Machine Learning Blog

MAY 9, 2023

In this post, we help you understand the Python backend that is supported by Triton on SageMaker so that you can make an informed decision for your workloads and achieve great results. It dynamically downloads models from Amazon S3 to the instance’s storage volume if the invoked model isn’t available on the instance storage volume.

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Flipboard

MARCH 27, 2023

torch.compile Over the last few years, PyTorch has evolved as a popular and widely used framework for training deep neural networks (DNNs). The success of PyTorch is attributed to its simplicity, first-class Python integration, and imperative style of programming. Jump Right To The Downloads Section What’s New in PyTorch 2.0?

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Data Science Dojo

JUNE 14, 2023

GPT is one of the most popular machine-learning models used for text processing. I t belongs to a class of models called “ Transformers ” which are classified among deep learning models. Pegasus Transformer This is a part of the Transformers library available in Python 3. And that was just one model.

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Data Science Dojo

JUNE 14, 2023

GPT is one of the most popular machine-learning models used for text processing. I t belongs to a class of models called “ Transformers ” which are classified among deep learning models. Pegasus Transformer This is a part of the Transformers library available in Python 3. And that was just one model.

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Data Science Dojo

JUNE 14, 2023

GPT is one of the most popular machine-learning models used for text processing. I t belongs to a class of models called “ Transformers ” which are classified among deep learning models. Pegasus Transformer This is a part of the Transformers library available in Python 3. And that was just one model.

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AWS Machine Learning Blog

MARCH 8, 2023

This post shows a way to do this using Snowflake as the data source and by downloading the data directly from Snowflake into a SageMaker Training job instance. We create a custom training container that downloads data directly from the Snowflake table into the training instance rather than first downloading the data into an S3 bucket.

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PyImageSearch

JANUARY 6, 2025

Python or R) to find the critical value from the -distribution for the chosen and degrees of freedom ( ). Performing the Grubbs Test In this section, we will see how to perform the Grubbs test in Python for sample datasets with small sample sizes. Note: We need to use statistical tables ( Table 1 ) or software (e.g., Thakur, eds.,

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Flipboard

OCTOBER 9, 2023

This would include steps related to downloading certain components, performing some commands, and anything that you would do on a simple command line to configure everything from scratch. It allows us to start API development within a few lines of simple Python code. the image). Let’s look at the Dockerfile now and go line by line.

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Dataconomy

AUGUST 15, 2024

Stable Diffusion is a deep-learning model that generates high-quality images based on text prompts. Here’s a step-by-step guide: Install Python : Ensure Python 3.8 You can download it from the official Python website. What is Stable Diffusion? or higher is installed on your system. safetensors `.

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Flipboard

SEPTEMBER 4, 2023

Home Table of Contents Getting Started with Docker for Machine Learning Overview: Why the Need? These images also support interfacing with the GPU, meaning you can leverage it for training your Deep Learning networks written in TensorFlow. What Are Containers? How Do Containers Differ from Virtual Machines? Follow along!

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Mlearning.ai

JANUARY 27, 2023

Save this blog for comprehensive resources for computer vision Source: appen Working in computer vision and deep learning is fantastic because, after every few months, someone comes up with something crazy that completely changes your perspective on what is feasible. How to read an image in Python using OpenCV — 2023 2.

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Flipboard

FEBRUARY 7, 2023

The following example illustrates Studio Lab running a Jupyter notebook that downloads TCIA prostate MRI data, segments it using MONAI, and displays the results using itkWidgets. Make sure to choose the medical-image-ai Python kernel when running the TCIA notebooks in Studio Lab.

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PyImageSearch

APRIL 24, 2023

This tutorial is primarily for developers who want to accelerate their deep learning models with PyTorch 2.0. In this series, you will learn about Accelerating Deep Learning Models with PyTorch 2.0. TorchDynamo and TorchInductor (primarily for developers) (this tutorial) To learn what’s behind PyTorch 2.0,

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AWS Machine Learning Blog

SEPTEMBER 20, 2023

AWS provides Deep Learning Containers (DLCs) for popular ML frameworks such as PyTorch, TensorFlow, and Apache MXNet, which you can use with SageMaker for training and inference. Finally, we deploy the ONNX model along with a custom inference code written in Python to Azure Functions using the Azure CLI. image and Python 3.0

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PyImageSearch

APRIL 7, 2025

Jump Right To The Downloads Section What Is Matrix Diagonalization? The code uses the NumPy library, which can be installed in your Python environment via pip install numpy. Download the code! Looking for the source code to this post? Thakur, eds.,

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PyImageSearch

DECEMBER 11, 2024

Home Table of Contents PNG Image to STL Converter in Python Why Convert a PNG to STL? To learn how to convert a PNG image to an STL file, keep reading! Jump Right To The Downloads Section Why Convert a PNG to STL? Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated?

Python 52

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AWS Machine Learning Blog

MAY 15, 2024

Optimized GEMM kernels ONNX Runtime supports the Microsoft Linear Algebra Subroutine (MLAS) backend as the default Execution Provider (EP) for deep learning operators. AWS Graviton3-based EC2 instances (c7g, m7g, r7g, c7gn, and Hpc7g instances) support bfloat16 format and MMLA instructions for the deep learning operator acceleration.

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PyImageSearch

FEBRUARY 20, 2023

Jump Right To The Downloads Section Learning JAX in 2023: Part 1 — The Ultimate Guide to Accelerating Numerical Computation and Machine Learning ?? Introduction As deep learning practitioners, it can be tough to keep up with all the new developments. Automatic Differentiation is at the very heart of Deep Learning.

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PyImageSearch

FEBRUARY 6, 2023

Furthermore, this tutorial aims to develop an image classification model that can learn to classify one of the 15 vegetables (e.g., If you are a regular PyImageSearch reader and have even basic knowledge of Deep Learning in Computer Vision, then this tutorial should be easy to understand. tomato, brinjal, and bottle gourd).

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PyImageSearch

JANUARY 1, 2024

Gemini Pro is now available in Bard through the MakerSuite UI and their Python Software Development Kit (SDK). Gemini Pro Vision API This section demonstrates how to use the Python SDK for the Gemini API, which provides access to Google’s Gemini LLMs. The image is then displayed in the Colab notebook. That’s not the case.

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AWS Machine Learning Blog

MAY 30, 2023

When an On-Demand job is launched, it goes through five phases: Starting, Downloading, Training, Uploading, and Completed. From a pricing perspective, you are charged for Downloading, Training, and Uploading phases. In this post, we discuss the Downloading and Training phases.

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IBM Data Science in Practice

APRIL 9, 2024

Instead, we use pre-trained deep learning models like VGG or ResNet to extract feature vectors from the images. Image retrieval search architecture The architecture follows a typical machine learning workflow for image retrieval. You can follow command below to download the data. Building the Image Search Pipeline 1.

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AWS Machine Learning Blog

OCTOBER 19, 2023

Customers increasingly want to use deep learning approaches such as large language models (LLMs) to automate the extraction of data and insights. For many industries, data that is useful for machine learning (ML) may contain personally identifiable information (PII). Download the SageMaker Data Wrangler flow.

Machine Learning 122

Machine Learning Machine Learning ML ML 122

Heartbeat

JULY 25, 2023

Introduction When it comes to practicing deep learning at home vs. industry, there’s a huge disconnect. TensorFlow itself comes with the Dataset API that allows you to simply download and train data with just a couple of lines of code. Yes, even in python (we will see this later). Learn how Comet can help you do this.

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AWS Machine Learning Blog

MAY 4, 2023

You can use ml.trn1 and ml.inf2 compatible AWS Deep Learning Containers (DLCs) for PyTorch, TensorFlow, Hugging Face, and large model inference (LMI) to easily get started. For the full list with versions, see Available Deep Learning Containers Images. petaflops of FP16/BF16 compute power.

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AWS Machine Learning Blog

APRIL 7, 2025

Discover Llama 4 models in SageMaker JumpStart SageMaker JumpStart provides FMs through two primary interfaces: SageMaker Studio and the Amazon SageMaker Python SDK. Alternatively, you can use the SageMaker Python SDK to programmatically access and use SageMaker JumpStart models. b64encode(img).decode('utf-8')

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AWS Machine Learning Blog

FEBRUARY 20, 2024

Download the model and its components WhisperX is a system that includes multiple models for transcription, forced alignment, and diarization. For smooth SageMaker operation without the need to fetch model artifacts during inference, it’s essential to pre-download all model artifacts. __dict__[WAV2VEC2_MODEL].get_model(dl_kwargs={"model_dir":

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AWS Machine Learning Blog

JUNE 6, 2023

Our next generation release that is faster, more Pythonic and Dynamic as ever for details. These are basically big models based on deep learning techniques that are trained with hundreds of billions of parameters. for high-performance distributed deep learning training. Refer to PyTorch 2.0:

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AWS Machine Learning Blog

JUNE 13, 2023

In this post, we demonstrate how to deploy Falcon for applications like language understanding and automated writing assistance using large model inference deep learning containers on SageMaker. SageMaker large model inference (LMI) deep learning containers (DLCs) can help. See the following code: %%writefile./code_falcon40b_deepspeed/serving.properties

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AWS Machine Learning Blog

OCTOBER 5, 2023

First, download the Llama 2 model and training datasets and preprocess them using the Llama 2 tokenizer. For example, to use the RedPajama dataset, use the following command: wget [link] python nemo/scripts/nlp_language_modeling/preprocess_data_for_megatron.py He focuses on developing scalable machine learning algorithms.

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AWS Machine Learning Blog

APRIL 19, 2023

The DJL is a deep learning framework built from the ground up to support users of Java and JVM languages like Scala, Kotlin, and Clojure. With the DJL, integrating this deep learning is simple. Our data scientists train the model in Python using tools like PyTorch and save the model as PyTorch scripts.

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