Model conversion file structure - Visual Studio Code

After creating the model project and running it several times, the file structure might look like this: In the model_project_name folder, workflows for each model are stored in a separate folder. requirements.txt: lists the dependencies required to run the workflow and the inference sample.

Convert a model with AI Toolkit for VS Code (Preview)

Model conversion is an integrated development environment designed to help developers and AI engineers to convert, quantize, optimize and evaluate the pre-built machine learning models on your local Windows platform.

Setup model conversion environment manually - Visual Studio Code

This article introduces how to manually set up Python environments for model conversion across different hardware targets, including CPU, QNN, AMD NPU, and Intel NPU. We recommend installing your environment in a Python virtual environment or a Conda environment.

Manage Jupyter Kernels in VS Code

Each Jupyter kernel has a Jupyter kernel specification, or Jupyter kernelspec, which contains a JSON file (kernel.json) with details about the kernel—name, description, and CLI information required to launch a process as a kernel.

Using Clang in Visual Studio Code

In this tutorial, you configure Visual Studio Code on macOS to use the Clang/LLVM compiler and debugger. After configuring VS Code, you will compile and debug a C++ program in VS Code. This tutorial does not teach you about Clang or the C++ language. For those subjects, there are many good resources available on the Web.

Visual Studio Code - Code Editing. Redefined

Use AI models like Claude Sonnet out of the box, or bring your own key to access models from Azure, Anthropic, Google, Ollama, OpenAI, and OpenRouter. Your codebase is indexed locally and remotely (on GitHub) to understand what's relevant, enabling fast, context-aware interactions.

Manage context for AI - Visual Studio Code

In this article, you learn how to manage context in chat, including how to use #-mentions to reference files, folders, and symbols, how to reference web content, or how you can use custom instructions to guide the AI's responses. VS Code automatically provides context to the chat prompt based on your current activity.

Editing Python in Visual Studio Code

Visual Studio Code is a powerful editing tool for Python source code. The editor includes various features to help you be productive when writing code. For more information about editing in Visual Studio Code, see Basic Editing and Code Navigation.

Configure C/C++ IntelliSense - Visual Studio Code

IntelliSense is a helpful tool built into VS Code that provides various code editing features to help you code faster and more efficiently. For example, code completion, parameter info, syntax highlighting, Code Actions (light bulbs), and member lists are all generated using IntelliSense.

Visual Studio Code debug configuration

In VS Code, there are two core debugging modes, Launch and Attach, which handle two different workflows and segments of developers. Depending on your workflow, it can be confusing to know what type of configuration is appropriate for your project.