robinyves

Learn to enhance LLM performance using test-time compute with parallel sampling, sequential revision, and process reward models for better reasoning.

Provides AI learning tips by demonstrating how to create custom LangChain agents with structured outputs using Pydantic models.

Learn to build Retrieval-Augmented Generation (RAG) applications using LangChain with Python and FAISS vector stores for enhanced AI retrieval.

Guide on efficiently fine-tuning large language models using LoRA adapters with Python code examples and configuration details.

Provides concise AI training tips from Andrej Karpathy, including starting with a tiny dataset to verify model and pipeline functionality.