#Prompt_Engineering

Question count - 0     Last updated    - V4 (26-Aug-2024)

Basic LLM Concepts	LLMs Types of LLMs How are LLMs Built? Vocabulary
Prompting	Basic Prompting Need for Prompt Engineering
Prompting	Basic Prompting Use Delimiters to distinguish the data from the prompt. Ask for Structured Output e.g. JSON, XML, HTML etc. Include style information to modify the tone of output. Give conditions to the model and ask if they are verified. Give successful examples of completing tasks then ask. Specify the steps required to perform a task. Instruct model to work out its own solution before giving answers. Iterate and Refine your prompts. Need for Prompt Engineering
Prompting Techniques	Role Prompting Few Shot Prompting Chain of Thought Prompting Zero Shot Chain of Thought Least to Most Prompting Dual Prompt Approach Combining Techniques Prompting Techniques Parts of a Prompt
Real World Usage Examples	Structured Data Inferring Writing Emails Coding Assistance Study Buddy Designing Chatbots
Pitfalls of LLMs	Citing Sources Bias Hallucinations Math Prompt Hacking
Improving Reliability	Prompt Debiasing Prompt Ensembling LLM Self Evaluation Calibrating LLMs Math
LLM Settings	Temperature Top P Other Hyperparameters
Image Prompting	Style Modifiers Quality Boosters Weighted Terms Fix Deformed Generations
Prompt Hacking	Prompt Injection Prompt Leaking Jailbreaking Defensive Measures O!ensive Measures

Prompt_Engineering
Question	Option A	Option B	Option C	Option D