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30 Days of LLMs: Day 7 —Deep Dive into LLM Sampling Techniques

For Day 7 of the 30 Days of LLMs, we dive into advanced LLM sampling, exploring temperature & top P techniques. Experience real model demonstrations and troubleshooting tips.
Created on December 8|Last edited on December 10
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Day 7: Deep Dive into LLM Sampling Techniques

Explore the realm of Large Language Models (LLMs) with Weights & Biases in the seventh segment of our complimentary online course, "Building LLM-Powered Apps." Our specialist, Darek Kleczek, will guide you through the complexities of sampling methods used in LLMs.

Chapter Highlights

  • Grasping Sampling Concepts in LLMs: Delve into the crucial role of sampling methods in text creation using LLMs.
  • Temperature and Top P Sampling Techniques: Discover two pivotal sampling strategies – temperature and top P – and their impact on the text generation process.
  • Live Examples of Sampling: Observe these sampling techniques being employed in practical scenarios with our Vinci 003 text model, and comprehend how varying configurations affect the results.
  • Solving Common Issues: Acquire knowledge on addressing API limit errors and other typical obstacles encountered in LLM applications.

Key Course Information

  • No deep machine learning knowledge is needed, just some familiarity with Python programming.
  • Strategies for continual enhancement of your LLM applications.
  • Unique perspectives on the LLM tools used by Weights & Biases.

Free Enrollment

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Preview of the Next Chapter

Don't miss our next chapter, where we will focus on creating a foundational LLM application, discussing essential elements like application architecture and beyond.
















Tags: ML News
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