Unlocking the Power of Language Models through Fine-Tuning and Efficient Transfer Learning

Fine-tuning and efficient transfer learning techniques have revolutionized natural language processing, enabling machines to understand and generate human-like text. PETL technologies like LORA and QLORA optimize the fine-tuning process. Quantization techniques reduce memory and computational requirements. Downstream tasks include sentiment analysis, named entity recognition, machine translation, text generation, text summarization, and question answering.