Introduction to LLM

Total of 7 articles available. Currently on page 1 of 1.

3.3 Fine-Tuning and Transfer Learning for LLMs: Efficient Techniques Explained

Learn how fine-tuning and transfer learning techniques can adapt pre-trained Large Language Models (LLMs) to specific tasks efficiently, saving time and resources while improving accuracy.
2024-09-14

2.3 Key LLM Models: BERT, GPT, and T5 Explained

Discover the main differences between BERT, GPT, and T5 in the realm of Large Language Models (LLMs). Learn about their unique features, applications, and how they contribute to various NLP tasks.
2024-09-10

2.0 The Basics of Large Language Models (LLMs): Transformer Architecture and Key Models

Learn about the foundational elements of Large Language Models (LLMs), including the transformer architecture and attention mechanism. Explore key LLMs like BERT, GPT, and T5, and their applications in NLP.
2024-09-06

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

A Guide to LLMs (Large Language Models): Understanding the Foundations of Generative AI

Learn about large language models (LLMs), including GPT, BERT, and T5, their functionality, training processes, and practical applications in NLP. This guide provides insights for engineers interested in leveraging LLMs in various fields.
2024-09-01

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SHO

CTO of Receipt Roller Inc., he builds innovative AI solutions and writes to make large language models more understandable, sharing both practical uses and behind-the-scenes insights.