Pretraining

As explained in Build a Website with ChatGPT

Pretraining is the initial training of a model on large amounts of data to learn general patterns before task-specific use.

How Build a Website with ChatGPT covers it

How deep it goes

Defines exposure, learned patterns, and next-word prediction, but stops short of describing training algorithms or model internals.

Examples

Uses sentence formation, next-word prediction, and exposure to programming code as concrete examples of learned patterns.

What it assumes

Assumes no technical background and defines pretraining through language patterns and next-word prediction.

What you can do after

Evaluate/understand why GPT can generate text and web-page code after learning broad patterns from large datasets.

How it connects

Connects large language models with language patterns, next-word prediction, transformers, and programming-code generation.

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Also explained in

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  Deep Learning with R, Third EditionUnsupervised pretraining is training a model on input data without manually supplied labels before adapting it to downstream tasks.
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  Deep Learning with Python, Third EditionThe initial large-scale training phase used to learn broad language representations before task-specific fine-tuning.
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  Build a Large Language Model (From Scratch)The initial training phase in which a language model learns general patterns from a large text corpus before task-specific adaptation.
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  Time Series Forecasting Using Foundation ModelsPretraining is initial training of a model on a large dataset to learn general patterns and relationships before applying it to specific tasks.
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  Inside Deep Learning: Math, Algorithms, ModelsA strategy of training a model on a source dataset before adapting it to a downstream task.
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  Build a Reasoning Model (From Scratch)The initial training stage in which a language model learns general statistical structure from large amounts of data before task-specific adaptation.
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  The Art of AI Product DevelopmentPretraining is the initial training of a model on broad data before adapting it to specific tasks or domains.
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  liveBookmanning.com
  How Large Language Models WorkPretraining is the initial training of a model on broad data before adapting it to particular tasks or applications.
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  Introduction to Generative AI, Second EditionThe initial training phase in which a model learns general representations or predictive behavior from a large corpus before task-specific adaptation.
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  LLMs in ProductionPretraining is the initial training of a model on a large, broad dataset before adapting it to a specific task or domain.
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  Sutskever's ListPretraining is the initial training of a model on a broad dataset before task-specific adaptation or evaluation.
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  liveBookmanning.com
  Data Without LabelsPretraining is an initial model-training stage that learns general patterns or representations before adaptation to a specific task.
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  liveBookmanning.com
  Reinforcement Learning from Human FeedbackPretraining is the initial large-scale optimization of a model on broad data, commonly through next-token prediction.

Compare how 14 books explain pretraining →

Related concepts

• foundational modelproduces · A base or foundation model is a pretrained model that provides learned parameters or capabilities as a starting point for reuse or adaptation to downstream tasks.
• pretrained modelproduces · A pretrained model is a machine-learning model whose parameters were learned through prior training before it is used or adapted for a subsequent task.
• next-token predictionuses · Next-token prediction is the task or training objective of estimating the token that follows a sequence, given its preceding tokens and any conditioning information.
• datasetuses · A dataset is an organized collection of related data items, records, or observations treated as a unit for storage, processing, analysis, or computation.
• zero-shot learningused by · Zero-shot learning is a setting in which a model performs a task or predicts categories without task-specific examples during training, adaptation, or inference, relying on learned knowledge and available task information.
• similarity searchused by · Similarity search is a retrieval technique that finds or ranks items by comparing their representations with a query according to a similarity or distance measure.

This explainer was generated by Manning's knowledge graph from the text of Build a Website with ChatGPT. The section links point to the parts of the book it draws on.