Trained over six hours for 4000 steps from a dataset of ~900 images from r/TwinksAndTwunks, r/CollegeBoys, some professional solo gay porn image albums, and a few other places I don't remember. Annotated using abliterated Gemma 4.Seems alright.If it helps anyone, here is the AI-Toolkit config I used:<pre><code>---
job: "extension"
config:
 name: "moss_men"
 process:
 - type: "diffusion_trainer"
 training_folder: "/workspace/output"
 sqlite_db_path: "./aitk_db.db"
 device: "cuda"
 trigger_word: null
 performance_log_every: 10
 network:
 type: "lora"
 linear: 64
 linear_alpha: 64
 lokr_full_rank: true
 lokr_factor: -1
 network_kwargs:
 ignore_if_contains:
 - "layers.22."
 save:
 dtype: "bf16"
 save_every: 250
 max_step_saves_to_keep: 4
 save_format: "diffusers"
 push_to_hub: false
 datasets:
 - folder_path: "/workspace/Images/Dataset"
 mask_path: null
 mask_min_value: 0.1
 default_caption: ""
 caption_ext: "txt"
 caption_dropout_rate: 0.05
 cache_latents_to_disk: true
 is_reg: false
 network_weight: 1
 resolution:
 - 1024
 controls: []
 shrink_video_to_frames: true
 num_frames: 1
 flip_x: false
 flip_y: false
 num_repeats: 1
 train:
 batch_size: 2
 bypass_guidance_embedding: false
 steps: 4000
 gradient_accumulation: 1
 train_unet: true
 train_text_encoder: false
 gradient_checkpointing: false
 noise_scheduler: "flowmatch"
 optimizer: "adamw8bit"
 timestep_type: "shift"
 content_or_style: "balanced"
 optimizer_params:
 weight_decay: 0.0001
 unload_text_encoder: false
 cache_text_embeddings: false
 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"
 logging:
 log_every: 1
 use_ui_logger: true
 model:
 name_or_path: "OpenMOSS-Team/MOSS-Image-Base"
 quantize: true
 qtype: "convrot8"
 quantize_te: true
 qtype_te: "convrot8"
 arch: "moss_image:base"
 low_vram: true
 model_kwargs:
 uncond_skip_layers:
 - 22
 compile: false
 layer_offloading: false
 layer_offloading_text_encoder_percent: 1
 layer_offloading_transformer_percent: 1
 sample:
 sampler: "flowmatch"
 sample_every: 250
 sample_start_step: 0
 width: 1024
 height: 1024
 samples:
 - prompt: "A man stands in front of a mirror in a bathroom, taking a selfie with a silver smartphone. He has short dark hair, a goatee, and a mustache. He is wearing a white tank top that is pulled up to expose his abdomen, which has a small patch of dark hair around the navel. His lower body is partially clothed in black pants, which are pulled down to reveal his genitals. His penis is erect, with the shaft and glans visible, and he is holding it with his right hand. The background features black tiled walls with white grout, and a white door is visible to the left. The lighting is bright, casting clear shadows and highlighting the textures of the tiles and the man's skin. The overall atmosphere is casual and intimate, capturing a private moment."
 width: 768
 height: 1024
 - prompt: "The image depicts a person standing in a laundry room, captured from the waist down. The individual is wearing a red short-sleeve shirt and light blue underwear with a gray waistband. They are holding a tennis racket with a black frame and white grip, gripping it with their right hand. The racket is positioned in front of their body, with the head angled downward. The person's penis is erect and visible through the open waistband of their underwear, pointing downward. The penis goes through the truss of the racket. The background includes a white washing machine and dryer stacked vertically, with various items on top of the dryer. The walls are plain and light-colored, and the floor appears to be a neutral tone. The lighting is bright, casting clear shadows and highlighting the textures of the clothing and the racket. The overall atmosphere is casual and candid, capturing a moment in a domestic setting."
 width: 768
 height: 1024
 neg: ""
 seed: 42
 walk_seed: true
 guidance_scale: 3
 sample_steps: 50
 num_frames: 1
 fps: 1
meta:
 name: "[name]"
 version: "1.0"
</code></pre>

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