I added a lot of furry images for training, but the results are not ideal.Due to limited GPU memory, the training resolution had to be kept low, and I used labels as prompts since I didn’t have time to convert them into natural language.Please don’t judge the quality of the base model by the performance of this LoRA.This is an experimental model that may generate NSFW content. The training data comes from an artist, so the model may be taken down later. It’s intended only for research and learning purposes.Honestly, I was just advised to give this a try, but the results might turn out pretty bad 😛I’m still pausing updates and treating this as a few simple experiments.For better results, please look forward to the edited version of Z-image and Z-Image-Base. The Z-image team is also considering doing an anime-style finetune—perhaps that will be the promised land?

Bara male [Z-image Turbo] (test)

<pre><code>---
job: "extension"
config:
 name: "my_first_lora_v2"
 process:
 - type: "diffusion_trainer"
 training_folder: "D:\\ai_training\\ai-toolkit\\output"
 sqlite_db_path: "./aitk_db.db"
 device: "cuda"
 trigger_word: "syj style"
 performance_log_every: 10
 network:
 type: "lora"
 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"
 push_to_hub: false
 datasets:
 - folder_path: "D:\\ai_training\\ai-toolkit\\datasets/2464453_training_data"
 mask_path: null
 mask_min_value: 0.1
 default_caption: ""
 caption_ext: "txt"
 caption_dropout_rate: 0.05
 cache_latents_to_disk: true
 is_reg: false
 network_weight: 1
 resolution:
 - 512
 - 768
 controls: []
 shrink_video_to_frames: true
 num_frames: 1
 do_i2v: true
 flip_x: true
 flip_y: false
 train:
 batch_size: 1
 bypass_guidance_embedding: false
 steps: 2000
 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: 0.0001
 unload_text_encoder: false
 cache_text_embeddings: true
 lr: 0.0001
 ema_config:
 use_ema: false
 ema_decay: 0.99
 skip_first_sample: false
 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: "uint4"
 quantize_te: true
 qtype_te: "qfloat8"
 arch: "zimage:turbo"
 low_vram: true
 model_kwargs: {}
 layer_offloading: true
 layer_offloading_text_encoder_percent: 1
 layer_offloading_transformer_percent: 0
 assistant_lora_path: "ostris/zimage_turbo_training_adapter/zimage_turbo_training_adapter_v2.safetensors"
 sample:
 sampler: "flowmatch"
 sample_every: 250
 width: 1024
 height: 1024
 samples:
 - prompt: ""
 - prompt: ""
 neg: ""
 seed: 42
 walk_seed: true
 guidance_scale: 1
 sample_steps: 8
 num_frames: 1
 fps: 1
meta:
 name: "[name]"
 version: "1.0"
</code></pre>

my_first_lora_v2_000001750.safetensors

Files with SHA256: 939239b06a358135a334d40ee1b61d5f9dbf1f2693770627d21fd2d806ade0df