Easily Create eye-catching images for pearl creature
Just dream up what you want and we optimize to get great images at scale. pearl creature is perfect for jellyfish, 人像, 閃亮, 珍珠, and 水母 images
Using colors as trigger words in the 1.0 version doesn't seem like a good idea, so version 2.0 uses other trigger words and increases the training steps.
Folder 10_mix_gost: 66 images found
Folder 10_mix_gost: 660 steps
Folder 25_gost: 5 images found
Folder 25_gost: 125 steps
Folder 25_mix_axolotl: 30 images found
Folder 25_mix_axolotl: 750 steps
Folder 25_mix_blueD: 30 images found
Folder 25_mix_blueD: 750 steps
Folder 25_mix_bug: 31 images found
Folder 25_mix_bug: 775 steps
Folder 25_mix_coral: 29 images found
Folder 25_mix_coral: 725 steps
Folder 25_mix_creature: 30 images found
Folder 25_mix_creature: 750 steps
Folder 25_mix_flower: 31 images found
Folder 25_mix_flower: 775 steps
Folder 25_mix_frog: 30 images found
Folder 25_mix_frog: 750 steps
Folder 25_mix_J: 30 images found
Folder 25_mix_J: 750 steps
Folder 25_mix_octopus: 30 images found
Folder 25_mix_octopus: 750 steps
Folder 25_mix_preal: 30 images found
Folder 25_mix_preal: 750 steps
Folder 25_mix_sea slug: 30 images found
Folder 25_mix_sea slug: 750 steps
Folder 25_mix_shark: 29 images found
Folder 25_mix_shark: 725 steps
Folder 25_mix_snow: 30 images found
Folder 25_mix_snow: 750 steps
Folder 25_mix_spring: 31 images found
Folder 25_mix_spring: 775 steps
max_train_steps = 28275
stop_text_encoder_training = 0
lr_warmup_steps = 0
Here is the trainer command as a reference. It will not be executed:
accelerate launch --num_cpu_threads_per_process=2 "train_network.py"
--pretrained_model_name_or_path="D:/ai/stable-diffusion-webui/models/Stable-diffusion/v1-5-pruned.safetensors"
--train_data_dir="D:/ai/test/image"
--resolution=768,768 --output_dir="D:/ai/test/model"
--logging_dir="D:/ai/test/log"
--network_alpha="128"
--save_model_as=safetensors
--network_module=networks.lora
--text_encoder_lr=5e-5
--unet_lr=0.0001
--network_dim=128
--output_name="25_preal_1v5_768_0001BD5e_NR128NA128off"
--lr_scheduler_num_cycles="5"
--learning_rate="0.0001"
--lr_scheduler="constant"
--train_batch_size="2"
--max_train_steps="28275"
--save_every_n_epochs="1"
--mixed_precision="bf16"
--save_precision="bf16"
--seed="1234"
--caption_extension=".txt"
--cache_latents
--optimizer_type="AdamW8bit"
--max_data_loader_n_workers="1"
--clip_skip=2
--bucket_reso_steps=64
--xformers
--bucket_no_upscale
See what else you can do with pearl creature
Create hundreds of images for pearl creature in minutes
Produce eye-catching images on pearl creature with our autoscale system. You can create thousands of images on top of our cluster to get images incredibly fast. No more waiting around on your local machine for results.
Test variants and ideas quickly with our csv system
Have a general idea you want to test, but its not coming out exactly as you want, use our mass generator import system to generate many variations to find the perfect image you are looking for. You can write in excel, csv, or any other tool that exports CSV.
Check out other related models: jellyfish, 人像, 閃亮, 珍珠, 水母
Save time and money
Its a hassle getting all of this setup, with the click of a button start creating images instantly and effortlessy to find the perfect visualizations for your project.
Better looking images than anywhere else
Don't waste time playing around with settings and configurations. We have optimized and fine-tuned pearl creature to get the best results.
Build a custom model on top of pearl creature
Like the results you see with pearl creature and want to build your own on top of it? No problem, we provide infrastructure to easily build on top of it. Just give us a few images and we will build a new model on top of it. (This feature is in private beta)
Test pearl creature against hundreds of models with one click
Use our omni prompt tool and compare pearl creature with any models you want. You just put in your prompts and select the models and it runs instantly.
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