This model is a combination of NaiveV2, NaiveV2Diff, and Vocoder. NaiveV2 and NaiveV2Diff is a cascaded training LYNXNet front stage and LYNXNet diffusion model. They are extremely small in size and highly efficient. You can train such a model by using configs/config_naivev2diff_comb.yaml and combining them with a fine-tuning vocoder using combo.py. fine-tuning vocoder ：https://github.com/openvpi/SingingVocoders

Shallow diffusion model: k_step_max=100 unit encoder: contentvec768l12 training 600000 steps without pretrain model network: 512*20 speaker1: opencpop speaker2: kiritan Naive model: unit encoder: contentvec768l12 training 200000 steps without pretrain model speaker1: opencpop speaker2: kiritan