Configure launch.json for C/C++ debugging in Visual Studio Code

Create a development container using Visual Studio Code Remote Development

Run a set of prompts with variables or function calls with an imported or synthetically generated dataset towards the selected models and parameters.

Learn how to fine-tune the Phi Silica model in Azure using a custom dataset, download the resulting LoRA adapter, and perform inference with the adapter.

Python data science tutorial demonstrating the use of common data science and machine learning libraries with Visual Studio code Jupyter Notebook support.

Connect over SSH with Visual Studio Code

Learn how to build machine learning applications in Azure Machine Learning using the Visual Studio Code extension

Evaluate AI models, prompts, and agents using AI Toolkit's comprehensive evaluation system. Import datasets, run evaluations with built-in evaluators like F1 score, relevance, coherence, and similarity, or create custom LLM-based and code-based evaluators. Visualize and compare results in tables and charts.

Visual Studio Code Remote Development Frequently Asked Questions (FAQ) for SSH, Containers, and WSL

Default settings in Visual Studio Code.