Converting dense Qwen2.5 models into Mixture-of-Experts architectures

A new conversion process yields Qwen2.5-1.5B-MoE models, including GGUF versions for local deployment. Benchmarks show the MoE conversion increases WikiText-2 perplexity by 41% and C4 perplexity by 45% compared to the original dense models.