Search Results for "code snippets"

Claude Code is an intelligent agentic coding assistant that lives in your terminal and understands your entire codebase. It helps developers code faster by executing routine tasks, explaining complex code snippets, and managing git workflows—all via natural language commands. Claude Code integrates seamlessly into your terminal, IDE, or GitHub by tagging @claude to interact with your code context.

This extension is for Tabnine’s Starter (free), Pro and Enterprise SaaS users only. Tabnine Enterprise users with the self-hosted setup should use the Tabnine Enterprise extension in the VSCode Marketplace. Tabnine is an AI code assistant that makes you a better developer. Tabnine will increase your development velocity with real-time code completions, chat, and code generation in all the most popular coding languages and IDEs. Whether you call it IntelliSense, intelliCode, autocomplete, AI-assisted code completion, AI-powered code completion, AI copilot, AI code snippets, code suggestion, code prediction, code hinting, content assist, unit test generation or documentation generation, using Tabnine can massively impact your coding velocity, significantly cutting down your coding time.

DeepSeek-Coder is a series of code-specialized language models designed to generate, complete, and infill code (and mixed code + natural language) with high fluency in both English and Chinese. The models are trained from scratch on a massive corpus (~2 trillion tokens), of which about 87% is code and 13% is natural language. This dataset covers project-level code structure (not just line-by-line snippets), using a large context window (e.g. 16K) and a secondary fill-in-the-blank objective to encourage better contextual completions and infilling. ...

...It contains guides, API references, and examples for developers building applications using Google’s large language models, text-to-image models, embeddings, and multimodal capabilities. The repository includes markdown source files that power the Google AI developer documentation site, as well as sample code snippets in Python, JavaScript, and other languages that demonstrate how to use Google’s Generative AI SDKs and REST APIs effectively.

...The project is a practical starting point for building AI-powered applications, serving as a foundation for experimentation and integration into larger projects. It simplifies onboarding by offering step-by-step setup instructions and ready-to-use code snippets that can be adapted for custom needs.

openai-cookbook is a repository containing example code, tutorials, and guidance for how to build real applications on top of the OpenAI API. It covers a wide range of use cases: prompt engineering, embeddings and semantic search, fine-tuning, agent architectures, function calling, working with images, chat workflows, and more. The content is primarily in Python (notebooks, scripts), but the conceptual guidance is applicable across languages.

This repository is a collection of useful jupyter notebooks, code snippets and example JSON files illustrating the use of Reinvent 3.2.

This repository is a curated collection of resources, papers, code, and summaries relating to human activity recognition/behavior recognition. It is not a single integrated software package but rather a knowledge base organizing feature extraction methods, deep learning approaches, transfer learning strategies, datasets, and representative research in behavior recognition. The repository includes links to code in MATLAB, Python, summaries of algorithms, datasets, and relevant research...