wereanimal_2.0
Details
| Model Type | LORA |
| Base Model | SD 1.5 |
| Published | 2023-04-05 |
| Trained Words | werenaimal werecreature Humanoid weredog weresloth weredeer werebird werelizard wereshark werecat werewolf weretiger werefox wereAxolotl werelion weremouse wererabbit werefrog werepanthers wereSideburns weresheep wereraccoon werebear weresnake werehorse wereCaterpillar werepig wereLeopard |
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About this version
Increased species and resolution compared to version 1.0
When using common species such as dogs tiger, cat......, you only need to add the species name without necessarily using a trigger word.
However, using a trigger word can more accurately call up specific data such as gender, caterpillars......
There are the following species:
-- were_\(dog\), were_\(male-dog\), were_\(female-dog\),weredog, dog,
--were_\(bird\), were_\(male-bird\), were_\(female-bird\), werebird, bird,
-- were_\(lizard\), were_\(male-lizard\), were_\(female-lizard\),werelizard, lizard,
--were_\(shark\),Same as above.......
--were_\(cat\),Same as above.......
--were_\(wolf\),Same as above.......
--were_\(tiger\),Same as above.......
--were_\(fox\),Same as above.......
--were_\(salamander\),Same as above.......
--were_\(lion\),Same as above.......
--were_\(mouse\),Same as above.......
--were_\(rabbit\),Same as above.......
--were_\(frog\),Same as above.......
--were_\(ox\),Same as above.......
--were_\(Chimpanzees\),Same as above.......
--were_\(horse\),Same as above.......
--were_\(weasel\),Same as above.......
--were_\(Caterpillar\),Same as above.......
--were_\(deer\),Same as above.......
--were_\(pig\),Same as above.......
--were_\(sloth\),Same as above.......
load StableDiffusion checkpoint Folder 10_cat-female_BD_1: 72 images found Folder 10_cat-female_BD_1: 720 steps Folder 10_wolf_male_BD: 75 images found Folder 10_wolf_male_BD: 750 steps Folder 11_tiger_male_BD: 73 images found Folder 11_tiger_male_BD: 803 steps Folder 125_ox_femail_BD: 6 images found Folder 125_ox_femail_BD: 750 steps Folder 125_rabbit_male_BD: 6 images found Folder 125_rabbit_male_BD: 750 steps Folder 12_cat-male_BD1: 66 images found Folder 12_cat-male_BD1: 792 steps Folder 13_fox-female_BD: 58 images found Folder 13_fox-female_BD: 754 steps Folder 13_fox-male_BD: 58 images found Folder 13_fox-male_BD: 754 steps Folder 150_pig: 1 images found Folder 150_pig: 150 steps Folder 16_salamander_BD: 49 images found Folder 16_salamander_BD: 784 steps Folder 20_lion-male_BD: 38 images found Folder 20_lion-male_BD: 760 steps Folder 20_mouse_male_BD: 38 images found Folder 20_mouse_male_BD: 760 steps Folder 20_rabbit_female_BD: 40 images found Folder 20_rabbit_female_BD: 800 steps Folder 21_bird-female_BD_1: 36 images found Folder 21_bird-female_BD_1: 756 steps Folder 23_mouse_female_BD: 33 images found Folder 23_mouse_female_BD: 759 steps Folder 23_werefrog: 33 images found Folder 23_werefrog: 759 steps Folder 250_hippo-female_BD: 3 images found Folder 250_hippo-female_BD: 750 steps Folder 25_lizard-female_BD: 30 images found Folder 25_lizard-female_BD: 750 steps Folder 25_tiger_female_BD: 30 images found Folder 25_tiger_female_BD: 750 steps Folder 26_Leopard_male_BD: 29 images found Folder 26_Leopard_male_BD: 754 steps Folder 26_Sideburns_female_BD: 29 images found Folder 26_Sideburns_female_BD: 754 steps Folder 27_werejellyfish: 28 images found Folder 27_werejellyfish: 756 steps Folder 29_shark_female_BD: 26 images found Folder 29_shark_female_BD: 754 steps Folder 29_wolf_female_BD: 26 images found Folder 29_wolf_female_BD: 754 steps Folder 30_Leopard_female_BD: 25 images found Folder 30_Leopard_female_BD: 750 steps Folder 33_deer-male_BD: 23 images found Folder 33_deer-male_BD: 759 steps Folder 33_sheep_male_BD: 23 images found Folder 33_sheep_male_BD: 759 steps Folder 357_sloth_BD: 2 images found Folder 357_sloth_BD: 714 steps Folder 375_Leopard_female_panthers_BD: 2 images found Folder 375_Leopard_female_panthers_BD: 750 steps Folder 40_lion-female_BD: 19 images found Folder 40_lion-female_BD: 760 steps Folder 44_raccoon_male_BD: 17 images found Folder 44_raccoon_male_BD: 748 steps Folder 50_bear_BD1: 15 images found Folder 50_bear_BD1: 750 steps Folder 50_raccoon_female_BD: 15 images found Folder 50_raccoon_female_BD: 750 steps Folder 50_sheep_female_BD: 16 images found Folder 50_sheep_female_BD: 800 steps Folder 58_Sideburns_male_BD: 13 images found Folder 58_Sideburns_male_BD: 754 steps Folder 68_snake_BD: 11 images found Folder 68_snake_BD: 748 steps Folder 69_Leopard_male_panthers_BD: 11 images found Folder 69_Leopard_male_panthers_BD: 759 steps Folder 75_ox_male_BD: 10 images found Folder 75_ox_male_BD: 750 steps Folder 7_dog-male_BD: 124 images found Folder 7_dog-male_BD: 868 steps Folder 84_Chimpanzees-male_BD: 9 images found Folder 84_Chimpanzees-male_BD: 756 steps Folder 84_horse-female_BD: 9 images found Folder 84_horse-female_BD: 756 steps Folder 84_weasel_female_BD: 9 images found Folder 84_weasel_female_BD: 756 steps Folder 84_wereCaterpillar: 9 images found Folder 84_wereCaterpillar: 756 steps Folder 8_bird-male_BD_1: 103 images found Folder 8_bird-male_BD_1: 824 steps Folder 94_deer-female_BD: 8 images found Folder 94_deer-female_BD: 752 steps Folder 9_dog-female_BD: 90 images found Folder 9_dog-female_BD: 810 steps Folder 9_lizard-male_BD: 86 images found Folder 9_lizard-male_BD: 774 steps Folder 9_shark_male_BD: 89 images found Folder 9_shark_male_BD: 801 steps max_train_steps = 108081 stop_text_encoder_training = 0 lr_warmup_steps = 0Here 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\100_wereanimal” –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=200 –output_name=“7_wereanimal_1v5_768_0001BD5e_NR128NA128off” –lr_scheduler_num_cycles=“3” –learning_rate=“0.0001” –lr_scheduler=“constant” –train_batch_size=“1” –max_train_steps=“108081” –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
Model description
It seems that the first version: wereanimal_1.0 has been removed from the website.
This is a LORA for animal humanoid .
Setting the weight to 0.2-0.8 will result in better performance.
Using the following Checkpoints model will result in more stable performance:
https://civitai.com/models/11718/dungeons-n-waifus-new-version-22
https://civitai.com/models/6250/dosmix
https://civitai.com/models/6925/realdosmix
https://civitai.com/models/7371/rev-animated
-You can also incorporate the Rola module of any real animal to achieve a more realistic effect.
-Using the pose controller can significantly improve the success rate.
It would be great if you could share your works using this module with me!