Adds a target="video" path that trains a LoRA directly against the configured
video model so it loads on the video pipeline (image LoRAs can't apply to a Wan
DiT). _train_wan: encodes stills as 1-frame latents via the Wan 3D VAE
(latents_mean/std normalized), encodes the prompt via UMT5, loads the
transformer expert(s) in 4-bit (QLoRA) with gradient checkpointing, adds PEFT
LoRA to the attention projections, and trains a rectified-flow loss. Handles
Wan2.2's dual experts (transformer + transformer_2) via boundary_ratio routing,
and saves both expert LoRA layers (falls back to high-noise only on older
diffusers). Reuses the queue, eviction, thermal checkpoints and progress.

LoraTrainRequest gains target/quantize_4bit/num_frames; base-path resolution
gains a "video" category so it resolves the video model entry.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>