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LLMs trained in stages: pretraining, fine-tuning, and reinforcement learning

By PulseAugur Editorial · [1 sources] ·

Large language models are trained in distinct stages to evolve from simple text predictors into helpful AI assistants. The initial pretraining phase involves the model learning to predict the next word from vast amounts of text. Subsequent stages, such as supervised fine-tuning and various forms of reinforcement learning (RLHF, RLAIF, rule-based scoring), refine the model's ability to follow instructions, provide helpful responses, and perform specific tasks like coding or math. AI

IMPACT Understanding LLM training methods is crucial for developers and researchers aiming to build more capable and aligned AI systems.

RANK_REASON The item explains the training process of LLMs, detailing different methods and stages. [lever_c_demoted from research: ic=1 ai=1.0]

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

LLMs trained in stages: pretraining, fine-tuning, and reinforcement learning

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The item explains the training process of LLMs, detailing different methods and stages. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · kanfu-panda ·

    How Are LLMs Trained?

    <blockquote> <p>The last post showed that an LLM is a program that keeps adding the next word. What turns it into an assistant that helps you write code is training in stages: first it reads huge amounts of text and learns to continue it, then it studies examples written by peopl…

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