An introductory guide to Large Language Models (LLMs) and their applications, including prompts, different types of LLMs, hallucination, and running LLMs on local machines. It also covers fine-tuning LLMs and optimization techniques.
Table of contents
What are LLMs?What can LLMs do?Putting LLMs to the testWhat are prompts?In-context learning (ICL)LLM parametersWhen to fine-tune?Optimization techniques for fine-tuningWhat is hallucination in LLMs?Running LLMs on local machinesConclusion1 Comment
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