Understanding the 4 Main Approaches to LLM Evaluation (From Scratch)
A guide to the four main methods for evaluating Large Language Models, including code examples and practical implementation details.
A guide to the four main methods for evaluating Large Language Models, including code examples and practical implementation details.
Explores three key methods to enhance LLM performance: fine-tuning, prompt engineering, and RAG, detailing their use cases and trade-offs.
A curated list of 12 influential LLM research papers from 2024, highlighting key advancements in AI and machine learning.
Analyzes the latest pre-training and post-training methodologies used in state-of-the-art LLMs like Qwen 2, Apple's models, Gemma 2, and Llama 3.1.