What is Prompt Engineering
Prompt Engineering - Query design
Designing queries or instructions to optimize LLM or VLM performance in multimodal tasks.
How It Works
Prompt engineering involves crafting queries or instructions to guide large language models (LLMs) or vision-language models (VLMs) in generating desired outputs. This process optimizes model performance by providing clear and contextually relevant prompts.
Technical Details
Effective prompt engineering requires understanding model behavior and capabilities. Techniques include using specific keywords, providing context, and iteratively refining prompts to achieve optimal results.
Best Practices
- Craft clear and contextually relevant prompts
- Consider model behavior and capabilities
- Iteratively refine prompts for optimal results
- Use specific keywords and context
- Regularly update prompt strategies
Common Pitfalls
- Using vague or ambiguous prompts
- Ignoring model behavior and capabilities
- Inadequate prompt refinement
- Poor keyword and context usage
- Lack of regular updates
Advanced Tips
- Use hybrid prompt techniques
- Implement prompt optimization
- Consider cross-modal prompt strategies
- Optimize for specific use cases
- Regularly review prompt performance