Prompt Engineering Best Practices for Gemma
📰 Dev.to AI
Learn prompt engineering best practices for Gemma to get quality output by matching its chat template and structuring instructions clearly
Action Steps
- Understand Gemma's chat template and its use of turn delimiters
- Structure instructions clearly to match Gemma's function-calling and reasoning features
- Apply guardrails to Gemma's function-calling and reasoning features where needed
- Test and refine prompts to optimize output quality
- Use practical prompting patterns to improve results
Who Needs to Know This
AI engineers and developers working with Gemma can benefit from this guide to improve their prompt engineering skills and get better results from the model
Key Insight
💡 Matching Gemma's chat template and structuring instructions clearly is key to getting quality output
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Improve your Gemma prompts with these best practices
Key Takeaways
Learn prompt engineering best practices for Gemma to get quality output by matching its chat template and structuring instructions clearly
Full Article
Getting quality output from Gemma isn't about clever tricks — it's about matching its exact chat template, structuring instructions clearly, and knowing where its function-calling and reasoning features need extra guardrails. This guide covers the practical prompting patterns that actually move the needle. Understand Gemma's Chat Template First Gemma models use and tokens as turn delimiters instead of the [INST]</
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