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EbookBell Team
4.3
78 reviewsYou'll learn how to use the power of pre-trained large language models for use cases like copywriting and summarization; create semantic search systems that go beyond keyword matching; build systems that classify and cluster text to enable scalable understanding of large amounts of text documents; and use existing libraries and pre-trained models for text classification, search, and clusterings.
This book also shows you how to
• 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
• Understand the architecture of underlying Transformer models like BERT and GPT
• Get a deeper understanding of how LLMs are trained
• Understanding how different methods of fine-tuning optimize LLMs for specific applications (generative model fine-tuning, contrastive fine-tuning, in-context learning, etc.)
