This article demonstrates a method for efficiently counting tokens in text for use with Large Language Models (LLMs) like Gemma in Rust. By leveraging the tokenizers and hf_hub crates, developers can perform token counting locally, avoiding slower network calls to external endpoints. This approach is ideal for offline usage, reduced complexity, and improved performance. The code snippet provides a practical example, while the article also addresses potential build issues on specific architectures, such as aarch64-pc-windows-msvc.
Learn to implement efficient syntax highlighting for Markdown files in Rust using pulldown-cmark and syntect. This guide covers parsing, code block identification, highlighting, and optimization techniques.
Tired of rust-analyzer recompiling your entire project after every save? This article explores the reasons behind this behavior and offers effective solutions. Discover how rust-analyzer's strict accuracy checks can lead to excessive recompilation, especially in large projects with numerous dependencies. We'll present practical workarounds, including disabling checkOnSave and configuring separate target directories, to streamline your workflow and boost your Rust development speed. Optimize your rust-analyzer configuration for a smoother and faster coding experience.
This blog post delves into the various methods for creating heterogeneous collections in Rust, where elements can be of different types. We discuss the pros and cons of approaches like using enums, traits, and the `Any` type. We explore how to leverage traits effectively with `Any` for type-safe downcasting. Additionally, we showcase a procedural macro technique to reduce boilerplate when implementing the `Component` trait for multiple structs. By comparing these methods, this article helps developers choose the most appropriate approach based on their specific project needs and desired level of flexibility.