New 8Buff_Real Stable Diffusion Released!

New model focused on realistic images, based on 8Buff_Gen model, our new 8Buff_Real SD 1.5 based model is available here: https://civitai.com/models/118761?modelVersionId=128937

Full and pruned versions available!

Notes and details:

This model does require a good deal of prompt crafting, the trade off is you have a lot of control on the images you create. I would recommend finding a prompt that generates the style and quality to your liking and saving it as a style.
Use 512x512 size for most consistent results. Does Well with 512x768, 768x512, and 768x768.
Recommended sampling methods: DPM++ 2S a Karras, Euler a, DDIM, DPM2 a Karras, DPM++2S a,

Improvements:

Requires less sampling steps to get quality images. Start at 30 and adjust from there.
Age consistency better with wider age range.
Fine tuning of prompts for nationality to get certain physical features.
General purpose realistic model with a fine level of control. Merged with a lot of different models, links below to those that were remembered or provided inspiration for direct training.
Great with deform and Automatic1111 Animator extension for GIFs or videos. See here for results: https://youtube.com/shorts/KwgcCbbQ35k?feature=share

Known issues:

Face distortion is still an issue but better than previous versions. Restore face and positive prompts address.
Tends to draw topless women about 10% of the time. This can be addressed by adding negative prompts nude and NSFw for image generation.
People tend to lean towards asian traits for eyes and hair. This can be addressed by adding nationality to the positive prompt. Nationalities that work with high consistency are: American, Indian, Nigerian, Japanese, and Ethiopian. Others such as European, Swiss, Mexican, work but not as consistently.
When using the Indian nationality prompt, it tends to give everyone a bindi. This can be addressed with adding (((bindi))) to your negative prompt.
Ages can be inconsistent sometimes with very young and very old people. Try positive prompts to like toddler, teen, adult, and elderly or provide a number (21 year-old).

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