LoRA-PAR Partitioned Training Achieves Half Parameter Usage and SOTA Performance Improvement!
Click the card below to follow「AI Vision Engine」public account ( Please add a note: direction + school/company + nickname/name ) Large-scale generative models like DeepSeekR1 and OpenAI-O1 benefit greatly from Chain of Thought (CoT) reasoning; however, improving their performance often requires massive datasets, large model sizes, and full parameter fine-tuning. While Parameter-Efficient Fine-Tuning (PEFT) helps … Read more
