[Verse 1] When you need an AI to understand your task The secret's in how you frame what you ask Zero-shot means no examples, just direct Few-shot gives samples for what you expect Chain-of-Thought breaks reasoning step by step Tree-of-Thought explores branches you've kept System prompts set the persona and tone Teaching language models how to respond on their own [Chorus] Large language models, powerful and bright Prompt them well and they'll get it right Fine-tune with LoRA when you need more RAG brings knowledge from your data store Evaluate outputs, measure what's true LLMs are waiting to work for you [Verse 2] When basic prompting isn't quite enough Fine-tuning helps when the task gets tough Full fine-tuning updates every weight But that's expensive, so don't hesitate To try LoRA, low-rank adaptation QLoRA too for parameter conservation Adapters add modules, keep the base intact While RLHF learns from human feedback [Chorus] Large language models, powerful and bright Prompt them well and they'll get it right Fine-tune with LoRA when you need more RAG brings knowledge from your data store Evaluate outputs, measure what's true LLMs are waiting to work for you [Bridge] RAG retrieves then generates with context Chunks your documents, embeds the text Reranking finds the most relevant parts While evaluation shows how well it starts MMLU and HumanEval test the skill GPQA challenges, LLM-as-judge will Red teaming finds the weaknesses and flaws Quality control for AI's cause [Verse 3] Build your RAG system piece by piece LangChain and LlamaIndex help increase Your document corpus understanding deep With metrics tracking what your models reap Chunking strategies split your data right Embedding models turn text into sight Vector databases store the representations Ready for retrieval in conversations [Chorus] Large language models, powerful and bright Prompt them well and they'll get it right Fine-tune with LoRA when you need more RAG brings knowledge from your data store Evaluate outputs, measure what's true LLMs are waiting to work for you [Outro] From zero-shot prompts to fine-tuned dreams RAG systems and evaluation schemes Master these techniques, you'll lead the way In the language model revolution today
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