🤗 PEFT welcomes new merging methods

The PEFT framework has introduced new merging methods for parameter-efficient fine-tuning, enhancing the integration of multiple models. These methods aim to improve performance on downstream tasks by effectively combining the strengths of different fine-tuned models while maintaining a low parameter footprint. This development is significant for practitioners as it enables more efficient model deployment and optimization, facilitating better resource utilization in large-scale AI applications.