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- Evaluating Large Language Models (LLMs) - RuTracker. org
Equips you with the knowledge and skills to assess LLM performance effectively Evaluating Large Language Models (LLMs) introduces you to the process of evaluating LLMs, Multimodal AI, and AI-powered applications like agents and RAG
- Quick Start Guide to Large Language Models (LLMs): ChatGPT, Llama . . .
Hi! You're welcome! Regarding the file ‘004 3 3 Building a Retrieval-Augmented Generation Bot with ChatGPT and GPT-4 mp4’, size 114271275 bytes and duration 19:46
- How Large Language Models Work Как . . . - RuTracker. org
How Large Language Models Work takes you inside an LLM, showing step-by-step how a natural language prompt becomes a clear, readable text completion Written in plain language, you’ll learn how LLMs are created, why they make errors, and how you can design reliable AI solutions Along the way, you’ll learn how LLMs “think,” how to
- [AI] Arun Raj Арун Радж - RuTracker. org
From unraveling the intricacies of LLM architecture to practical applications like code generation and AI-driven recommendation systems, readers will gain valuable insights into implementing LLMs in diverse projects
- Raschka S. - Build a Large Language Model [2025, PDF, ENG]
In Build a Large Language Model (from Scratch) bestselling author Sebastian Raschka guides you step by step through creating your own LLM Each stage is explained with clear text, diagrams, and examples
- [AI] Esposito F. - RuTracker. org
Artificial Intelligence expert Francesco Esposito illustrates several scenarios for which a LLM is effective: crafting sophisticated business solutions, shortening the gap between humans and software-equipped machines, and building powerful reasoning engines
- Hands-On Large Language Models - RuTracker. org
• Build advanced LLM pipelines to cluster text documents and explore the topics they belong to • Build semantic search engines that go beyond keyword search with methods like dense retrieval and rerankers • Learn various use cases where these models can provide value
- [AI] Trivedi Anand Триведи Ананд - RuTracker. org
В основе этой книги лежит одна идея: как может начать свой путь в ИИ каждый, кто хочет? Как можно разобраться в сложных концепциях llm, генеративного ИИ и диффузионных моделей?
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