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Oct 1, 2024
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2 changes: 1 addition & 1 deletion book/en/week06/session2.md
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Expand Up @@ -392,6 +392,6 @@ for temp in temperatures:

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## 9. Closing Remarks
## Conclusion
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suggestion (documentation): Consider enhancing the conclusion with a brief summary of key points

To make the conclusion more valuable, consider adding a concise recap of the main concepts covered in this session. This will reinforce the learning and provide a quick reference for readers.

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## Conclusion
## Conclusion
In this session, we explored:
- The importance of sampling methods in LLM APIs
- Key parameters like temperature and top-p
- Strategies for balancing creativity and coherence
- Techniques for tailoring output to specific formats
Understanding these concepts is crucial for leveraging LLMs effectively.


Understanding and effectively using sampling methods is essential for harnessing the full potential of LLM APIs. By mastering these parameters, you can generate text that meets specific requirements for creativity, coherence, and format. Continue to experiment and explore the possibilities offered by these powerful tools.
2 changes: 1 addition & 1 deletion book/ko/week06/session2.md
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## 9. 마무리 발언
## 결론

샘플링 방법을 이해하고 효과적으로 사용하는 것은 LLM API의 잠재력을 최대한 활용하는 데 필수적입니다. 이러한 매개변수를 마스터함으로써 창의성, 일관성, 형식에 대한 특정 요구사항을 충족하는 텍스트를 생성할 수 있습니다. 계속해서 실험하고 이 강력한 도구들이 제공하는 가능성을 탐구하세요.