[256-WF-SAEHD-DF-UD] 预训练100w+训练141w共241w次迭代 6G显存可以8bz

个人通过自己的电脑和租赁的云服务器跑的模型分辨率是256，WF
该模型是从外网下载的预训练模型，本身的预训练模式已经跑了100w次，
又使用了自己分割的素材跑了141w迭代，也就是100w加141w=241w次迭代
模型本身我用1060-6G可以跑到10bz,但有概率OOM,如果有条件可以使用linux跑
下面的详细介绍是训练模式下的迭代次数。

模型介绍：================== Model Summary ===================
==
==          Model name: 256wf_SAEHD
==
==    Current iteration: 1411533
==
==—————- Model Options —————–
==
==          resolution: 256
==          face_type: wf
==    models_opt_on_gpu: True
==                archi: df-ud
==             ae_dims: 256
==             e_dims: 64
==             d_dims: 64
==          d_mask_dims: 22
==    masked_training: True
==          eyes_prio: False
==          uniform_yaw: False
==          lr_dropout: n
==          random_warp: True
==          gan_power: 0.0
==    true_face_power: 0.0
==    face_style_power: 0.0
==       bg_style_power: 0.0
==             ct_mode: none
==             clipgrad: False
==             pretrain: False
==    autobackup_hour: 0
== write_preview_history: False
==          target_iter: 0
==          random_flip: False
==          batch_size: 10
==
==—————— Running On ——————
==
==       Device index: 0
==                Name: NVIDIA GeForce GTX 1060
==                VRAM: 6.00GB
==
====================================================