A single Lora to allow prompting of mini giantess size people that appear 6-30+ feet tall. The goal is to teach SD to tweak the scale of the background and provide full body poses.
V3 LyCoris:
Try 0.3-0.85 Strength, DPM++ 2M Karrras
What's New:
· Re-trained as a LyCoris, it's WAY BETTER. Less chaotic, more flexible, preserves model style.
· Expanded training data. Expanded on v2 training data from 278, 768x768 images to 896 images up to 768x1360. Added "macrogts" training images. Also see version notes.
Re-tagged trigger words to better prompt approximate scaling using mg-sg guide:
tallgts: Taller than average
minigiantess: Giantesses 7' to 12' tall
mesogts: Giantesses 12'to 50' tall
macrogts: Giantesses 50' to 500' tall
Also re-tagged training data by subject:
V2 Lora:
Try 0.2-0.85 Strength, lower is better for realism.
What's New:
· Re-trained as a Lora.
· Upscaled training images to 768x768
V1.2 - Older: Hypernetwork
A hyper-network to allow prompting of mini giantess size people that appear 6-30+ feet tall. The goal is to teach SD to tweak the scale of the background and provide full body poses.
See version list to pick anime or realism styles. Unfortunately LoRa testing trained poses but not the sense of scale. Instead, v1.2 attempts to provide a more stable, adaptable hyper-network. Try ~0.7 strength for realism, or ~0.3 for Grapefruit.
Although no prompt keyword is needed, try "minigiantess" and specifying a pose: standing, sitting, kneeling, crouching, full body portrait, long shot, head touching ceiling, laying, etc. Best results are to turn off hyper-network for final image cleanup.
v1.2 - Realism
Trained on Delibratev1.1 in SD 2.1. Same training data, but works significantly better in SD 2.1 and still functions in SD 1.5.6.
v1.2 - Grapefruit
Trained on Grapefruit V4 in SD 2.1 to provide anime illustration styles. See version notes.
v1.1 and Older
Doesn't work well on SD 2.1. Tested on SD 1.5.6 on Automatic1111.
Try using 0.6 strength.
Other process tips: 30 steps/DDIM to generate poses, then move to img2img and reduce hyper-network strength ~0.3.
Trained on Delibratev1.1 in SD 1.5.6. Hypernetwork potentially works to a lesser extent on other models.
Training notes:
· v1 - 100,000 steps, 1 epoch, wide net. ~100 images focused on a single subject indoors with BLIP tagging.
· v1.1 - 100,000 steps, 1 epoch, wide deep and bottle-necked, ~140 images, some with two subjects and outdoors backgrounds.
· v1.2 Grapefruit - 20,000 steps, 4 epochs, wide deep and bottle-necked with scaled LR. Same training images as v1.1.
· v1.2 Realism - 20,000 steps, 4 epochs, wide deep and bottle-necked with scaled LR. Same training images as v1.1.
