Model Merging Insights

Sachin discusses the challenges of model merging for adaptation, emphasizing the effectiveness of ensembling models at inference time over collapsing them into a single model. The importance of maintaining specialized models for specific tasks like non-toxic text and chat is highlighted, shedding light on the nuances of merging models effectively in NLP tasks.