The LLM training process consists of two primary stages: (1) Pre-Training, a massive-scale, self-supervised process where the model optimizes a next-token prediction objective to acquire linguistic knowledge and reasoning abilities; and (2) Supervised Fine-Tuning (SFT), where the pre-trained model is trained on a smaller, high-quality dataset of labeled instruction-response pairs to adapt to human intent.

Authors

• Person: Not available Organization: arXiv
  A Survey on the Theory and Mechanism of Large Language Models

Sources

• A Survey on the Theory and Mechanism of Large Language Models arxiv.org arXiv via serper

Referenced by nodes (3)

• Pre-training concept
• supervised fine-tuning concept
• reasoning capabilities concept