!! THIS MODEL IS NOT MINE !!
Original Owner: SinisterBoy
Details
Type
LORA
Downloads
1.613
Uploaded
Jul 23, 2023
Base Model
SD 1.5
Trigger Words
VPL
Hash
AUTOV2
7FC807A7EC
1 File
Reviews
8 version ratings
5 out of 5
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About this version
Trained on 139 images, 2 repeats for 50 epochs. Saved and sampled the model for every epoch completed. Epoch #22 out of 50.
[[subsets]] num_repeats = 2 keep_tokens = 1 caption_extension = ".txt" shuffle_caption = true flip_aug = false is_reg = false image_dir = "E:/Projects/vpl_lora/v7/dataset" [noise_args] [logging_args] [general_args.args] pretrained_model_name_or_path = "E:/Projects/v1-5-pruned.safetensors" mixed_precision = "fp16" seed = 23 clip_skip = 1 xformers = true max_data_loader_n_workers = 1 persistent_data_loader_workers = true max_token_length = 225 prior_loss_weight = 1.0 cache_latents = true max_train_epochs = 50 [general_args.dataset_args] resolution = 512 batch_size = 2 [network_args.args] network_dim = 16 network_alpha = 9.0 [optimizer_args.args] optimizer_type = "AdamW8bit" lr_scheduler = "cosine" learning_rate = 0.0001 [saving_args.args] output_dir = "E:/Projects/vpl_lora/v7/build" save_precision = "fp16" save_model_as = "safetensors" output_name = "hardvpl" save_every_n_epochs = 1 [bucket_args.dataset_args] enable_bucket = true min_bucket_reso = 256 max_bucket_reso = 1024 bucket_reso_steps = 64 [sample_args.args] sample_prompts = "E:/Projects/vpl_lora/v7/prompt.txt" sample_sampler = "ddim" sample_every_n_epochs = 1 [optimizer_args.args.optimizer_args] weight_decay = "0.1" betas = "0.9,0.99"
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SinisterBoy
Joined Jul 14, 2023
#100
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Gives dudes a big raging hard-on in their pants.
In the prompt, use the trigger word "vpl" and maybe what kind of pants/underwear the subject is wearing (so far underwear works best.) Throwing the word "bulge" in there may yield better results under certain conditions. It seems to do better with semi-realistic models. The weight is most effective around 0.7-1.0.
P.S. this is my very first LoRA, and I intend to release an improved version in the future, so stay tuned! If you've generated any good VPLs, please post or share as I would love to add it to the training data for v2.
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Discussion
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Inshirtandtie
24 days ago
What was your dataset like? I’ve been trying to improve the outcome of unzipped pants but not sure how to describe it when training.
3
diffusiondudes
24 days ago
omg yes we needed this!! thank you
❤️
2
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netaenetae
6 hours ago - v1.0
5.0
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HardVPL - Visible Penis Line - v1.0 | Stable Diffusion LoRA | Civitai
About this version
Trained on 139 images, 2 repeats for 50 epochs. Saved and sampled the model for every epoch completed. Epoch #22 out of 50.
[[subsets]] num_repeats = 2 keep_tokens = 1 caption_extension = ".txt" shuffle_caption = true flip_aug = false is_reg = false image_dir = "E:/Projects/vpl_lora/v7/dataset" [noise_args] [logging_args] [general_args.args] pretrained_model_name_or_path = "E:/Projects/v1-5-pruned.safetensors" mixed_precision = "fp16" seed = 23 clip_skip = 1 xformers = true max_data_loader_n_workers = 1 persistent_data_loader_workers = true max_token_length = 225 prior_loss_weight = 1.0 cache_latents = true max_train_epochs = 50 [general_args.dataset_args] resolution = 512 batch_size = 2 [network_args.args] network_dim = 16 network_alpha = 9.0 [optimizer_args.args] optimizer_type = "AdamW8bit" lr_scheduler = "cosine" learning_rate = 0.0001 [saving_args.args] output_dir = "E:/Projects/vpl_lora/v7/build" save_precision = "fp16" save_model_as = "safetensors" output_name = "hardvpl" save_every_n_epochs = 1 [bucket_args.dataset_args] enable_bucket = true min_bucket_reso = 256 max_bucket_reso = 1024 bucket_reso_steps = 64 [sample_args.args] sample_prompts = "E:/Projects/vpl_lora/v7/prompt.txt" sample_sampler = "ddim" sample_every_n_epochs = 1 [optimizer_args.args.optimizer_args] weight_decay = "0.1" betas = "0.9,0.99"
