02_large_language_models

Large Language Models (LLMs)

Introduction

Large Language Models (LLMs) are powerful AI systems that can understand and generate human-like text. They have revolutionized natural language processing and are the foundation of many modern AI applications.

Topics Covered

1. Algorithms

• Byte-Pair Encoding (BPE)
• Self-Supervised Learning
• Supervised Learning (Instruction Tuning)
• Reinforcement Learning

2. Architectures

• Transformer Architecture
• Encoder-Decoder
• Causal Decoder
• Prefix Decoder

3. Training Techniques

• Data Collection and Preprocessing
• Model Configuration
• Model Training
• Fine-tuning

4. Optimization

• Model Pruning
• Knowledge Distillation

5. Tools and Libraries

• Hugging Face Transformers
• TensorFlow
• PyTorch
• LangChain
• LlamaIndex

Learning Resources

Online Courses

• LLM University by Cohere
• Large Language Model Course by Maxime Labonne

Documentation and Guides

• Hugging Face Transformers Documentation
• PyTorch Documentation
• TensorFlow Documentation
• LangChain Documentation
• LlamaIndex Documentation

Research Papers and Articles

• Large language model - Wikipedia
• Large language model training: how three training phases shape LLMs
• Exploring Architectures and Configurations for Large Language Models