E-Books →Designing Large Language Model Applications A Holistic Approach to LLMs

Experienced ML researcher Suhas Pai offers practical advice on harnessing LLMs for your use cases and dealing with commonly observed failure modes. You'll take a comprehensive deep dive into the ingredients that make up a language model, explore various techniques for customizing them such as fine-tuning, learn about application paradigms like RAG (retrieval-augmented generation) and agents, and more.
* Understand how to prepare datasets for training and fine-tuning
* Develop an intuition about the Transformer architecture and its variants
* Adapt pretrained language models to your own domain and use cases
* Learn effective techniques for fine-tuning, domain adaptation, and inference optimization
* Interface language models with external tools and data and integrate them into an existing software ecosystem