Lora to make vagina in various positions.
Trigger word: Pussy
V2: This version was trained with z-image base and works very well with z- image turbo.
Works well with 1 to 1.5 lora strength.
V1: I recommend a weight around 0.6, with res_2s sampler, beta57 scheduler and 4+ steps.
See the showcase to see some types of prompts for certain positions.
My first attempt at this. I don't know if it's good, but have fun!
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FAQ
Comments (32)
Holy moly! 20k steps! great job! on example pics. I hit 10k steps and my vaginas were still deformed so I just gave up. What were your settings?!
Here is mine that failed
--- job: "extension" config: name: "P0ssy3" process: - type: "diffusion_trainer" training_folder: "D:\\StabilityMatrix-win-x64\\ai-toolkit\\output" sqlite_db_path: "./aitk_db.db" device: "cuda" trigger_word: "p0ssy" 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: 10 save_format: "diffusers" push_to_hub: false datasets: - folder_path: "D:\\StabilityMatrix-win-x64\\ai-toolkit\\datasets/p0ssy" mask_path: null mask_min_value: 0.1 default_caption: "woman exposing her breasts and vagina " caption_ext: "txt" 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 flip_x: true flip_y: false train: batch_size: 1 bypass_guidance_embedding: false steps: 5000 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: 0.1 unload_text_encoder: false cache_text_embeddings: true lr: 0.0002 ema_config: use_ema: false 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" do_differential_guidance: true differential_guidance_scale: 3 model: name_or_path: "Tongyi-MAI/Z-Image-Turbo" quantize: false qtype: "qfloat8" quantize_te: true qtype_te: "qfloat8" arch: "zimage:turbo" low_vram: false model_kwargs: {} layer_offloading: false layer_offloading_text_encoder_percent: 1 layer_offloading_transformer_percent: 1 assistant_lora_path: "ostris/zimage_turbo_training_adapter/zimage_turbo_training_adapter_v1.safetensors" sample: sampler: "flowmatch" sample_every: 250 width: 1024 height: 1024 samples: - prompt: "full body shot of a nude woman with red hair, at the park, sitting down and spreading her legs apart exposing her breasts and vagina" - prompt: "a full body shot of a woman holding a coffee cup, in a beanie, sitting at a cafe with her legs spread wide apart exposing her breasts and vagina" neg: "" seed: 42 walk_seed: true guidance_scale: 1 sample_steps: 8 num_frames: 1 fps: 1 meta: name: "[name]" version: "1.0"
im training at 1280 and i dont get any deformed my dataset images are 2800x4300
Ты неправильно тренируешь, выбираешь влагалище крупным планом на белом фоне, штук 10–15 с разных ракурсов, а потом добавляешь уже девушек с разными позами, так как в модели нет нормального ассета, то приходится подучивать её.
Только указывай правельный ракурс, что бы не получилост влагалище вверх ногами
I only used the default settings from aitoolkit with 20k steps.
Yeah, around 10k steps, the vaginas weren't that great yet, but around 15k they started to get better.
终于有人做这个了
First model and it's great, well done Po! Whens the WF's coming ;)
When you are looking for a good Z-Workflow just use this one:
https://civitai.com/models/2174733/
Why all loras (not just your) dramatically drop down quality of image?
Click the image, it's just the preview that looks weird!
That's because they're training the model with the turbo version and not the base version; they need the base version for it to work properly.
It's the de-distillation adapter LoRA used to allow training the turbo model. Once the base model becomes available, these will all need to be re-trained, but they should improve quality (in theory).
Also, seems like with turbo if your LORA power exceeds 1 it falls apart. 2lora works, but both at 0.5
@Simplec222 but base is not available yet ?
@Gericho222 Yes realistic models can't handle high weights, z-image is no exception. I tried recent ZiT LoRa at 0.25 and it works well most of the time. 0.6 suggested in the description seems too high for this model.
@CyberAImania zImage Turbo = merge(Z-Image Base + lightning loras);
Z-Image-BaseTo be released 👍
Unnaturally shaved. Where's the hair?
Not bad. 5/10.
Z-Image is definitely struggling in the female anus department... is screws up the pussies too but the anuses are literally non-existent.
Why is the result I achieved much worse compared to the example picture you provided?
Try to use the settings that I used to make the pictures.
Lora weight: 0.6;
sampler: res_2s;
scheduler: beta57;
steps: 9;
resolutions: 1080x1920 or 1536x1536 (720x1280 or 1024x1024 works too)
Most lora loaders for Z-image do nothing, and most people haven't noticed. Turn the strength to 11.0... If your image looks fine, your lora loader isn't working.
It hasn't even been out a full week and we already have full blown nudity LoRAs. LOL
Gotta goonie googoo ;)
I cant recommend this one, like most of zLoras, the quality drop just kills zImage...still worth just stay in flux or sdxl.
Its coz they all have it in their heads that training on a few images at 512x512 resolution gives good results! ... Im using min 50 highest quality images @ 1536 x 1536 native Z-Image resolution. seeing improvements in images rather than pure destruction!
@ronikush Nope. My dataset is composed by the "few" number of 500 images 2048x2048 (aitoolkit resizes down to 1536x1536 btw).
The drop of quality happens because we are training on the turbo version and not the base version; We need the base version for it to work properly.
training data is actually just a workflow; not the image set.
Does not work well with character lora's at higher strengths
it works well with the main ZIT model using res2s,3s_beta57, Beta57 generates lots of blotchy noise people like it ass skin tesxture, eventho it's aweful, this lora smoothens that agressive blochiness out, that's why it pairs well with beta57 or anything that creates blotchy noise. with other models you're gnna have to go down to 0.2 0.16, tho, u ar reducing the efectivness. so...weight your options
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Turbo Pussy Z - v1.0 - ZIT - pussy.safetensors











