This article explores how to implement a retriever over a knowledge graph containing structured information to power RAG (Retrieval-Augmented Generation) applications.
This article provides a comprehensive guide on fine-tuning the Llama 3.1 language model using Unsloth for efficient parameter-efficient training. It covers concepts like supervised fine-tuning, LoRA, QLoRA, and practical steps for training on a high-quality dataset.
Meta releases Llama 3.1, its largest and best model yet, surpassing GPT-4o on several benchmarks. Zuckerberg believes this marks the 'Linux moment' in AI, opening the door for open-source models to flourish.
