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What is chain of thought (CoT) prompting?

Chain of thought (CoT) is a prompt engineering technique that enhances the output of large language models (LLMs), particularly for complex tasks involving multistep reasoning.

Why is chunking important in RAG applications?

As you go deeper down the rabbit hole building LLM-based applications, you may find that you need to root your LLM responses in your source data. Fine

An Introductory Guide to Fine-Tuning LLMs

Fine-tuning Large Language Models (LLMs) has revolutionized Natural Language Processing (NLP), offering unprecedented capabilities in tasks like language translation, sentiment analysis, and text generation.

Fine-Tuning LLMs: Overview, Methods & Best Practices

Fine-tuning is the process of adjusting the parameters of a pre-trained large language model to unlock the full potential of LLMs in specific domains or applications.

Embeddings: The Language of LLMs and GenAI

To fully understand the potential of LLMs, you need to understand the concept of embeddings, the language of GenAI and LLMs, and how they can be used to solve business problems.