Dick Pic by IsnAI

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About:

Hello!

Have you ever been embarrassed or insecure about taking a picture of your 🐥 and sending it to someone?

Your problems are over!

Now you can just generate as many super realistic dongs as you want with this LoRA and spread them around. 😂

It was trained in 768x768, using captions and 166 (for now) images.

As usual, I make a test version without enhancing the photos, to assess viability. This one seems promising, so I'm going to upscale the dataset and add more content (God only knows when, because I have ADHD).

DO NOT FORGET THE DASHES IN PROMPT if you want to replicate the images I did.

The demo images aren't edited, but they are cherry-picked and generated in A1111 WebUI (v1.8 RC), using hires-fix (0.25 ~ 0.50 denoising), 4x_NMKD-Siax_200k (or 4x-UltraSharp) upscaler.

Suggested Settings for Inference:

Model: PicX_real

Positive: dick-pic, large penis, holding-a-thick-staff, first-person-pov, every-day, (((Ultra-HD-quality-details))) <lora:Dick_Pic_by_IsnAI:1:0.7)

Negative: morbide-body-parts, snap-fingers:2, apoplexy, wrong-placed-limbs

Sampler: DPM++ 2M Karras

Steps: 28

CFG: 67 got best results, but also works with 56

Resolution: 512x768

LoRA Weights: 1:0.7

Note¹: As you can see, the LoRA tag has two weights: <lora:Dick_Pic_by_IsnAI:1:0.7)
This is a feature of the A1111 (which many people aren't aware of), but you can set separate weights for the UNet and the Text Encoder. The TE is always a pain in the ass to get the training right, so it's usually better to reduce its weight in the inferences rather than having it undertrained.

Note²: You will see big variations in style and images depending on the base model used and minor adjustments in resolution.

Note³: If your images are getting weird and bizarre, you probably didn't reduce the TE weight. If you aren't using A1111 WebUI, you can do the common weight reduction: <lora:Dick_Pic_by_IsnAI:0.7), but you will need to test which weight will suit better.

Triggers:

Main Tags Used on Training: dick-pic, penis, first-person-pov, holding-a-thick-staff

Secondary Tags Used on Training: hairy, shaved, uncut, view-from-the-side, legs, hand, fingers, feet, toes