Introduction to LLM

Total of 5 articles available. Currently on page 1 of 1.

3.0 How to Train Large Language Models (LLMs): Data Preparation, Steps, and Fine-Tuning

Learn the key techniques for training Large Language Models (LLMs), including data preprocessing, forward and backward propagation, fine-tuning, and transfer learning. Optimize your model’s performance with efficient training methods.
2024-09-11

1.3 Differences Between Large Language Models (LLMs) and Traditional Machine Learning

Understand the key differences between Large Language Models (LLMs) and traditional machine learning models. Explore how LLMs utilize transformer architecture, offer scalability, and leverage transfer learning for versatile NLP tasks.
2024-09-05

1.2 The Role of Large Language Models (LLMs) in Natural Language Processing (NLP)

Discover the impact of Large Language Models (LLMs) on natural language processing tasks. Learn how LLMs excel in text generation, question answering, translation, summarization, and even code generation.
2024-09-04

1.1 Understanding Large Language Models (LLMs): Definition, Training, and Scalability Explained

Explore the fundamentals of Large Language Models (LLMs), including their structure, training techniques like pre-training and fine-tuning, and the importance of scalability. Discover how LLMs like GPT and BERT work to perform NLP tasks like text generation and translation.
2024-09-03

1.0 What is an LLM? A Guide to Large Language Models in NLP

Discover the basics of Large Language Models (LLMs) in natural language processing (NLP). Learn how LLMs like GPT and BERT are trained, their roles, and how they differ from traditional machine learning models.
2024-09-02

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