Prison Pipeline (gay)

This model will help you draw male/male intimate encounters.

The model follows an ambiguous prison setting, meaning that this setting tends to not be overtly apparent unless you choose to lean into it through prompting. Adding a dynamic and immersive prison setting will require a stand-alone LoRA. Stay tunned for that, it's in the pipeline.

Trigger: zpipeline

This project marks a departure from my previous training style and philosophy. "Secondary Triggers" are no longer necessary. Use the trigger word zpipeline and then prompt whatever you might want in your image. The model will create your prompt through the lens of the concept/s that it has learned, those concepts being related to male/male intimate encounters. I will add prompt ideas that are relevant to the concept.

Positive Prompt Ideas:

yaoi - bara - inmate - prisoner - white_t-shirt - green_pants - prison_cell - prison_shower - anal - rough_sex - deep_penetration - sex_from_behind - standing_sex - bent_over - elbows_on_table - elbows_on_bed - arched_back - lying, on_bed, on_stomach - prone_bone - on_side - spooning - on_back - missionary - legs_up - knees_to_chest - kneeling - doggystyle - male_spitroast - mmm_threesome -fellatio - irrumatio - facial - tongue_out - anilingus - bullying - wince - grimace - moaning - foreboding - emotional - intense

*One prompt strategy would be to structure the prompt similar to this example -
yaoi, "add a few, concise, natural language prompts describing what you would like the image to depict", LoRA tag, no comma, space, trigger word, comma, "a series of tokens or prompts that add specific elements and or reinforce your natural language description and or the concept of this model" -
yaoi, there are two inmates in a prison_cell getting to know each other, they are undressing each other as a matter of politeness, lora:Pipeline2:1 zpipeline, white_t-shirt, green_pants, undressing_another, erection_under_clothes, nervous, shy, excited, implied_yaoi, intense,

Negative Prompt Ideas

1girl - pussy - breasts - twins - hetero - bad anatomy - worstquality - out of focus - blurry - low quality - bad proportions - mutated - poorly drawn face - extra limb - mutation - ugly - disfigured - deformed - bad body - missing fingers - long body - size_difference

*It may be a good strategy to avoid using negative prompts preemptively. They could potentially create a problem in your image where one would not have otherwise materialized. Use negative prompts as a reaction to counter things that you do not like in the images you have previously generated in your current workflow.

The example images for v2 were created with the following checkpoints -
NTR MIX | illustrious-XL | Noob-XL

Spike Driver
Starstruck

VAE

Liquid111VAE

SDXL VAE

********************************************************************************************************Note the width/height as they are not a standard size. 1216x832 is not an aesthetic ratio, so I bump 832 up to 896 which gives images a more pleasing ratio of approximately 3:4. I don't know if using my models with other dimensions, apart from the three I list below, warps images because I only ever use 1:1 or 3:4/4:3.
The following section contains information that is merely a suggestion for those whom might be new to image generation or just looking for some guidance. Many other settings for these parameters will also work.
Clip Skip: 1
CFG: 3-15
LoRA Strength: 1.0 (+/-)
Sampling Method: Euler - DPM++ SDE - DPM++ 2M
Schedule type: Karras
Sampling Steps: 20-45 (+/-)
Width/Height: 1024x1024, 1216x896, 896x1216

********************************************************************************************************This is a concept LoRA that has been trained on images of anatomically correct males of various ethnicities, ages, and body types. All images used in the data set were my own original artwork and were generated using Stable Diffusion SDXL. (Not the base model itself, but a checkpoint that was fine tuned from the SDXL base model.) This is noted because SDXL LoRAs work better when they are trained on SDXL generated images. Think of it like the training to create the LoRA being in a language Stable Diffusion is already fluent in.