Heeeeyyyy!!!
For those of you that do not know. She is an artic wolf who starts out as a spoiled brat that cannot act but can sing good.
Tips and Tricks
If you get a human or partial, try adding "wolf girl" or "animated wolf girl".
Using "paws" instead of "hands" can make her hands more accurate. (even though I trained using "handpaws"
Sampler and Scheduler Combos for Z-Image
dpmpp_2m_sde & beta
dpmpp_2m_sde & simple
dpmpp_sde & beta
dpmpp_sde & simple
res_multistep & simple
Anyways, I have spent a good while trying to fine tune the dataset and the training parameters.
I am open to any suggestions on improving the model.
If you create an image of Porsha that looks movie accurate, I might add it to the dataset and toss some yellow buzz your way.
This cannot be used for any commercial purposes since I do not own the character. This is purely for fun. I have only posted this on Civitai.
Description
Trained using Ostris AI Toolkit:
linear: 32
linear_alpha: 32
conv: 16
conv_alpha: 16
lokr_full_rank: true
lokr_factor: -1
network_kwargs:
ignore_if_contains: []
save:
dtype: bf16
save_every: 250
max_step_saves_to_keep: 4
save_format: diffusers
datasets:
mask_min_value: 0.1
caption_dropout_rate: 0.05
cache_latents_to_disk: false
is_reg: false
network_weight: 1
resolution:
- 512
- 768
- 1024
controls:
shrink_video_to_frames: true
num_frames: 1
do_i2v: true
train:
batch_size: 1
bypass_guidance_embedding: false
steps: 2800
gradient_accumulation: 1
train_unet: true
train_text_encoder: false
gradient_checkpointing: true
noise_scheduler: flowmatch
optimizer: adamw8bit
timestep_type: weighted
content_or_style: balanced
optimizer_params:
weight_decay: 0.01
unload_text_encoder: false
cache_text_embeddings: false
lr: 0.0001
ema_config:
use_ema: true
ema_decay: 0.99
skip_first_sample: true
force_first_sample: false
disable_sampling: false
dtype: bf16
diff_output_preservation: false
diff_output_preservation_multiplier: 1
diff_output_preservation_class: person
switch_boundary_every: 1
loss_type: mse
model:
name_or_path: Tongyi-MAI/Z-Image-Turbo
quantize: true
qtype: qfloat8
quantize_te: true
qtype_te: qfloat8
arch: zimage:turbo
low_vram: true
layer_offloading: false
layer_offloading_text_encoder_percent: 1
layer_offloading_transformer_percent: 1