Java on Visual Studio Code Frequent Asked Questions and Troubleshooting Guide

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

Use custom dataset to fine-tune a generative AI model in the Azure cloud or locally with GPUs. Deploy the fine-tuned model to the Azure cloud or download incremental files from fine-tuned model.

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

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

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.

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

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Create a development container using Visual Studio Code Remote Development

Connect over SSH with Visual Studio Code