Creating natively coherent characters using general model checkpoints like SDXL, Pony, or Flux is inherently difficult because these models are trained on vast, diverse datasets without any persistent sense of character identity. As a result, features such as facial structure, hairstyle, or clothing tend to vary between generations, making it hard to maintain visual or stylistic consistency across images. The most reliable solution is to train dedicated LoRA models or carefully mix existing ones to encode specific character traits and ensure coherence. However, with the removal of celebrity-based LoRA models and other identity-focused datasets, achieving this level of character consistency has become significantly more challenging for creators.

The goal of the GSMILF series of LoRA models is to overcome this limitation by offering several pre-created, coherent fictional character LoRAs based on a mix of fictional and real inspirations. These LoRA models have been optimized for use with the Indecent (Realism for Pony) model but can also be used effectively with other Pony-derived models.

GSMILF-002 : Valentina

Valentina is a 30-year-old with a captivating presence. She has long, wavy dark brown hair that flows naturally, framing her face, and deep brown eyes that exude a playful charm. Her skin tone is a warm olive with a scattering of freckles across her cheeks and shoulders. Valentina is a popular influencer known for her beauty and lifestyle content, with a following of over 3 million on social media platforms. She shares makeup tutorials, skincare routines, and personal vlogs, often collaborating with cosmetic brands to engage her dedicated audience.

Recommended parameters

Checkpoint : Indecent (Realism for Pony)

Steps : 25

Sampler : DPM++2M Karras or DPM++3M Exponential

CFG Scale : 5.0

Clip : -2

Pre-Prompt : score_9, score_8_up, score_7_up, source_photo, 1girl, gsmilf002

Negative prompt : score_6, score_5, score_4, score_1, score_2, score_3, source_pony, source_furry, source_anime, source_cartoon, greyscale, text, watermark, lowres, jpeg-artifacts, strabism, heterochromia, fused elements, low quality, poor quality, bad eyes, bad anatomy, unnatural teeth, normal quality, censored, poorly drawn eyes, poorly rendered eyes, 3D