Ltx23 Surfaces Realism LoRA

--- license: other license_name: ltx-2-community-license license_link: https://huggingface.co/Lightricks/LTX-2/blob/main/LICENSE.txt base_model: Lightricks/LTX-2.3 tags: - ltx-video - ltx-2.3 - lora - text-to-video - realism - textures - diffusion-single-file --- # LTX-2.3 Surface Realism LoRA — video-branch, rank 32 Kills the plastic. LTX-2.3 (and the image models feeding it first frames) defaults to clean, smooth, showroom-new surfaces: pristine asphalt, unmarked walls, grounds that read as rendered geometry. This LoRA is an always-on **materials prior**: cracked wet asphalt stays cracked and wet, concrete gets pores and rust streaks, floors scuff, weeds mat, wood grains. It pushes the render toward surfaces that have existed in weather. ## No trigger word — by design The training captions name only material, condition, framing, and light — they deliberately contain **zero realism vocabulary** ("photoreal", "detailed", "8k" never appear). The realism therefore trains as unconditional LoRA behavior instead of a phrase you have to remember to include. Load it at 1.0 and write your prompts normally; concrete material nouns in your prompt ("scuffed linoleum", "rust-streaked concrete") still help composition, as they always did. ## Voice/audio safe by construction 1,152 LoRA tensors, all in the video branches — `attn1` (480), `attn2` (480), `ff` (192). **Zero audio-touching tensors**: dialogue, voices, and accents render byte-identical with or without this LoRA. Verified alongside an audio-branch accent LoRA in the same stack with no interference. ## Usage - Strength **1.0** in any LTX-2.3 LoRA loader. - Compatible with the LTX-2.3 22B family: stock distilled 1.1 and the JoyAI-Echo surgical merges (bf16 / fp8 / INT8 / GGUF via fuse-at-load). - If you render dialogue: keep your workflow at **24 fps** — not for this LoRA's sake, but because off-24 fps drifts every LTX voice toward British/Australian regardless of prompt (verified 2026-07-30). ## Training - ai-toolkit on an RTX 3090, rank 32 / alpha 32, 3,000 steps, lr 1e-4, qfloat8. Base: stock `ltx-2.3-22b-distilled-1.1`. Loss 1.01 -> 0.52. - Data: 1,076 hand-curated surface plates (from a 1,900+ candidate pool) generated with Z-Image Turbo specifically for this training — grounds, walls, floors, and weathered materials under varied light. Every image is s...