<h2 id="detaches-the-foreskin-and-&quot;peels-()&quot;-it-back-to-about-the-middle-of-the-penis">Detaches the foreskin and "peels (剝)" it back to about the middle of the penis</h2><ul><li><s>Trigger word for prompt: </s><s>detached foreskin</s>The v5.9-Anima slider doesn't need a trigger word anymore</li><li>Check my images for prompts / LoRA combinations</li><li>See the "About this version" information on the right for which LoRA strength to use</li><li>Workflows should be embedded in the newest images</li><li>Generated using ComfyUI</li><li>Please share your creations so I can see how well it's working with other styles! :)</li></ul><h1 id="general-training-settings">General Training Settings</h1><ul><li>LoRA_Easy_Training_Scripts to train the model</li><li>DatasetProcessorDesktop to crop and manage images</li><li>BooruDatasetTagManager to manage tags</li><li>See "About this version" for individual training details (right side)</li></ul><h1 id="v5.9-training-details">v5.9 Training Details</h1><ul><li>Fizgig-8.9.95 to train the model (.json available under version info tab)</li><li>Fizgig-8.9.95 to mask and resize images to 1MP</li><li>BooruDatasetTagManager to manage tags (the goat)</li><li>Works alright. Wish it actually had more levels of control, but I didn't have in-between images for training and there's only "positive and negative" folders for training.</li></ul><h1 id="v4.6-training-details">v4.6 Training Details</h1><ul><li>LoRA_Easy_Training_Scripts to train the model (.toml available under version info tab)</li><li>DatasetProcessorDesktop to crop and sort images</li><li>BooruDatasetTagManager to manage tags</li><li>Trained on different artist, grouped into subsets</li><li>Only 700 Steps (got lucky?)</li><li>Size of penis may be difficult to control at times</li></ul><h1 id="v3.2-and-v3.3-training-details">v3.2 and v3.3 Training Details</h1><ul><li>Set of 222 images, Repeats 2, Batch Size 4, Epochs 40 total but it only made 38?</li><li>Best results around 14 epochs (-0014) = ~6214 steps of training?<ul><li>It didn't seem too overtrained even after 40 epochs</li></ul></li><li>LoRA Type: LyCORIS/LoCon for smaller file size</li><li>Lower Network Rank = Lower File Size</li><li>Prodigy Optimizer automatically adjusts learning rate during training</li></ul><h1 id="v2.0-lora-training-details">v2.0 LoRA Training Details</h1><ul><li>Set of 240 images, Repeats 5, Epochs 6</li><li>Instance Prompt: detached foreskin, Class Prompt: penis</li><li>LoRA Type: standard</li><li>Max Train Steps: 7200 (because = 240x5x6)</li><li>bf16 precision</li><li>SDXL enabled, resolution of 1024x1024</li><li>Buckets enabled, don't upscale resolution. Resolution min: 256, max: 4096</li><li>Optimizer: Adafactor, args: scale_parameter=False relative_step=False warmup_init=False</li><li>LR Scheduler: constant</li><li>Learning Rate: 0.000025, Text Encode Rate: 0.0001, Unet Learning Rate: 0.0001</li><li>Network Rank: 64, Alpha: 1 &lt;-- mess with these settings later, they seem important</li><li>Saved every 1 epoch, best results around 3 epochs (-0003) = ~3600 steps of training<ul><li>Doesn't affect style too hard, appears with low weight (0.5), can go to very high weights (2.0) without completely destroying image</li></ul></li><li>(other settings didn't seem too important yet?)</li></ul>P.S. This is my first concept (idk what im doing most of the time). If you have any tips or advice, please comment on this model or DM me. It will improve this model and future ones that I make.Thank you!

Detached / Peeled Foreskin Penis (剝けチン / ズル剝け) [IllustriousXL / PonyXL]

Recommended strength for this version: -1.1 to 1.1No trigger word necessary, but adding penis and foreskin helps. Slider doesn't work exactly how I want it to, but it is what it is.Used Fizgig-8.9.95 to train this Anima slider LoRA. Masked training was quite helpful as it doesn't impact the rest of the image's style. Took a few attempts to figure out how to get the settings right. Basically to introduce a new concept, you need to ramp up the learning rate slowly, then decay with cosine to capture fine details and help with the slider. Only trained on 11 paired images (22 images total) with an associated mask for each image.Training data can be extracted from the .safetensors file, but here it is anyway. Don't mind the LORA_NAME value since I changed the metadata later before posting.<pre><code>{
 "LORA_OUTPUT_DIR": "C:\\AI\\Fizgig-8.9.95\\output_loras\\foreskin_slider_v1.9",
 "LORA_NAME": "foreskin_slider_v1.9",
 "TRAIN_SUBFOLDERS": true,
 "LEARNING_RATE": "0.000025",
 "ADAPTIVE_LR": false,
 "ADAPTIVE_LR_MIN": "1e-5",
 "ADAPTIVE_LR_MAX": "4e-4",
 "NETWORK_DIM": "8",
 "NETWORK_ALPHA": "4",
 "MAX_TRAIN_EPOCHS": "500",
 "SAVE_EVERY_N_EPOCHS": "10",
 "SAVE_LATER": true,
 "SAVE_UNTIL_EPOCH": "50",
 "SAVE_EVERY_AFTER": "1",
 "SEED": "1337",
 "CONTEXT_LORA_PATH": "",
 "CONTEXT_LORA_STRENGTH": "1.0",
 "DATASET_MEGAPIXELS": "1.0",
 "NETWORK_TYPE": "LoRA (standard)",
 "LOKR_FACTOR": "8",
 "FAMILY_EMA": "0.98 (recommended)",
 "KREA2_LOSS_WATCH": true,
 "KREA2_PER_IMAGE_LR": false,
 "KREA2_WARMUP_LOOK": false,
 "KREA2_AUTO_RECAPTION": false,
 "RECAPTION_FIRST": "Training caption (viewpoint-aware)",
 "RECAPTION_SECOND": "Exhaustive detail",
 "FAMILY_SLIDER_SOURCE": "Photo pairs",
 "FAMILY_SLIDER_DIR": "C:\\AI\\LoRA-Training\\detached_fskin\\slider-sets\\neg1",
 "FAMILY_SLIDER_CAPTION": "foreskin",
 "FAMILY_SLIDER_BASE": "",
 "FAMILY_SLIDER_POS": "",
 "FAMILY_SLIDER_NEG": "",
 "FAMILY_SLIDER_GUIDANCE": "2",
 "FAMILY_SLIDER_ANCHORS": "",
 "FAMILY_SLIDER_ANCHOR_WEIGHT": "1",
 "FAMILY_FT_ROTATIONS": "10",
 "FAMILY_FT_SAVE_EVERY": "1",
 "FAMILY_FT_ROTATE_EVERY": "1",
 "FAMILY_FT_MAX_PARTS": "Auto - as few windows as fit",
 "FAMILY_FT_FUSED": true,
 "FAMILY_FT_REG_DIR": "",
 "FAMILY_FT_REG_MULT": "0.2",
 "BLOCKS_SWAP": "Auto (detect from GPU)",
 "FAMILY_PRECISION": "Auto (fits your free VRAM)",
 "COMPILE_BLOCKS": "Auto",
 "SAVE_STATE": true,
 "SAVE_STATE_ON_TRAIN_END": true,
 "KEEP_LAST_N_STATES": "2",
 "OPTIMIZER_TYPE": "adamw",
 "OPTIMIZER_ARGS": "",
 "GRADIENT_ACCUMULATION": 1,
 "MAX_GRAD_NORM": 1,
 "DATASET_CAPTION_EXT": ".txt",
 "ENABLE_BUCKET": true,
 "BUCKET_NO_UPSCALE": true,
 "LR_SCHEDULER": "cosine",
 "LR_WARMUP_STEPS": "550",
 "METADATA_TITLE": "",
 "METADATA_AUTHOR": "",
 "METADATA_DESCRIPTION": "",
 "METADATA_LICENSE": "",
 "METADATA_TAGS": "",
 "METADATA_TRIGGER_PHRASE": "",
 "METADATA_THUMBNAIL": "",
 "ENABLE_CACHE": true,
 "MASKED_TRAINING": true,
 "MASK_FLOOR": "0.1 (recommended)",
 "MASK_PRIOR": "Off",
 "FAMILY_SUBJECTS": "1 subject",
 "FAMILY_SUBJECT_KIND": "From its captions",
 "FAMILY_SUBJECT_KIND2": "From its captions",
 "FAMILY_SUBJECT_KIND3": "From its captions",
 "FAMILY_SUBJECT_KIND4": "From its captions",
 "FAMILY_PEOPLE_MODE": "Off - a normal LoRA",
 "FAMILY_MP_MANUAL": false,
 "FAMILY_MP_FACECROPS_FIRST": true,
 "FAMILY_SUBJECT_FIX": false,
 "FAMILY_CONCEPT_BALANCE": false,
 "FAMILY_DOP_TRIGGER": "",
 "FAMILY_DOP_CLASS": "",
 "FAMILY_DOP_TRIGGER2": "",
 "FAMILY_DOP_CLASS2": "",
 "FAMILY_DOP_TRIGGER3": "",
 "FAMILY_DOP_CLASS3": "",
 "FAMILY_DOP_TRIGGER4": "",
 "FAMILY_DOP_CLASS4": "",
 "FAMILY_FT": false,
 "FAMILY_SLIDER": true,
 "FAMILY_EDIT": false,
 "MINIMAX_CONCEPT_DIRS": [
 ""
 ]
}</code></pre>

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