Large-language-models

LoRA fine-tuning enables efficient model customization by reducing memory usage and trainable parameters. Learn how adapter layers optimize training on consumer GPUs.

Vector embeddings are numerical representations that capture semantic meaning. This guide explains how mathematical vectors enable AI to process data relationships.

Retrieval-Augmented Generation connects AI models to private data to reduce hallucinations. This guide explains how RAG provides accurate and up-to-date answers.

Pydantic AI is a Python framework that uses data validation to build reliable AI agents. This guide explains how to use type hints to ensure structured LLM outputs.

This guide explains how vLLM accelerates Large Language Model serving using PagedAttention to optimize memory management and reduce latency for hardware setups.