Building Large Language Model Applications

👉The book provides a solid theoretical foundation of what LLMs are, their architecture. With a hands-on approach we provide readers with a step-by-step guide to implementing LLM-powered apps for specific tasks and using powerful frameworks like LangChain.

What you will learn

》Explore the core components of LLM architecture, including encoder-decoder blocks and embeddings

》Understand the unique features of LLMs like GPT-3.5/4, Llama 2, and Falcon LLM

》Use AI orchestrators like LangChain, with Streamlit for the frontend

》Get familiar with LLM components such as memory, prompts, and tools

》Learn how to use non-parametric knowledge and vector databases

》Understand the implications of LFMs for AI research and industry applications

》Customize your LLMs with fine tuning

》Learn about the ethical implications of LLM-powered applications

☆ https://towardsai.net/book

💢https://github.com/PacktPublishing/Building-LLM-Powered-Applications


#Machine_learning #LLM #Ai

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