Large Language Models

An LLM is a neural network trained on massive text data to understand and generate human language. Models like GPT-4, Claude, and Llama can perform translation, summarization, coding, reasoning, and more.

Training from scratch requires enormous compute resources. However, fine-tuning existing models on custom data is accessible with consumer GPUs. Techniques like LoRA and QLoRA make fine-tuning efficient.

Reinforcement Learning from Human Feedback is a technique to align LLMs with human preferences. Human raters rank model outputs, and the model is trained to produce responses that match those preferences.

Open-source models (Llama, Mistral) offer full control and lower costs at scale. Proprietary models (GPT-4, Claude) offer higher capability with simpler deployment. Consider your use case, budget, and data privacy needs.