Ellie_TLOU_XL is an identity‑focused SDXL LoRA trained on approximately 80 original images, all created exclusively from scratch for this dataset. No downloaded material or external images were used. Every image was generated, selected, and refined manually to ensure full control over identity, lighting, and consistency.

The dataset includes:

• high‑quality portraits

• half‑body shots

• neutral and environmental lighting

• narrative scenes

• recognizable locations inspired by the videogame’s world, enhancing atmosphere and contextual coherence

Training was performed on SDXL and intentionally stopped at 1750 steps, the optimal point before overfitting. This preserves:

• natural skin texture

• stable proportions

• strong identity consistency

• zero artifacts

• reliable performance even under complex lighting

Best Checkpoint: The model performs exceptionally well with SDXL Base, achieving maximum identity fidelity and the most natural rendering. It also works with other neutral checkpoints, but SDXL Base remains the recommended choice.

Recommended Strength:

• 0.75 → maximum stability; ideal for half‑body, narrative scenes, and complex environments

• 0.85 → professional sweet spot; strong identity with natural skin

• 0.9 → maximum safe strength; extremely faithful identity without introducing artifacts

Ideal Use Cases:

• Excellent for portraits (highest likeness, clean skin, precise details)

• Very good for half‑body shots (stable proportions, consistent identity)

• Reliable in narrative scenes (environment, dramatic lighting, post‑apocalyptic mood)

Notes: This LoRA was designed to deliver a coherent, realistic identity representation, improving the character’s depiction compared to many existing models. The dataset is entirely original, created by Sero, with no downloaded or copyrighted material.