From the course: Rust LLMOps

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Rust for large language models (LLMs)

Rust for large language models (LLMs) - Rust Tutorial

From the course: Rust LLMOps

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Rust for large language models (LLMs)

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- [Instructor] Rust components are very favorable to using large language models. Let's go ahead and talk about these particular components step by step. In a Rust compiler, the borrow checker is going to prevent race conditions and unsafe memory access bugs. It also is able to have ownership system automatically free memory when the objects go out of scope, so there's no need for manual memory management. And also, the compile time checks will find errors before the code is deployed, making sure that you have a very robust large language model deployment. In terms of the modular components here next, the tokenize is going to convert the text into a numerical ID for word embeddings. The embedding layer would map the words to high dimensional dense vectors. And the transform layer is going to use neural network models for processing text. And so this modular design allows the Rust traits to mix and match particular components. If we get into threads here next, lightweight Rust threads…

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