Explore JLama, a cutting-edge inference engine designed to empower Java developers with native AI capabilities. Discover how this innovative tool brings the power of large language models directly into the Java ecosystem without the need for GPUs. Learn about JLama's support for popular open models like Llama, Gemma, and Mixtral, and its utilization of the new Vector API in Java 21 for enhanced performance. Delve into key features such as advanced model support, tokenizer compatibility, and implementation of state-of-the-art techniques including Flash Attention, Mixture of Experts, and Group Query Attention. Understand how JLama integrates with the LangChain4j project and complements JVector's Java native vector search capabilities to create a comprehensive AI stack for Java. Gain insights into JLama's technical intricacies, practical applications, and witness a live demonstration showcasing its potential to revolutionize Java-AI integration.
Jlama: A Native Java LLM Inference Engine
Overview
Syllabus
Jlama: A Native Java LLM inference engine by Jake Luciani
Taught by
Devoxx