Large Language Models for IT Pros with Seth Juarez
RunAs Radio
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Getting the Right Output from Language Models
The speaker explores the concept of getting the right output from large language models, highlighting the discrepancy between mathematically correct answers and human perspective. They discuss the use of temperature to warp the output distribution and the process of fine tuning for better results. The chapter concludes by suggesting the influence of specific prompts to increase the likelihood of accurate answers.
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