get_model_info again skips model_index.json resolution entirely when
override_pipeline_cls_name is set, so overrides keep working for local
checkpoints without a diffusers model_index (and trigger no downloads).
Replace the nine copy-pasted kandinsky5 detectors with a parameterized
factory (identical matching semantics) and add a dedicated I2V Lite distilled
entry + preset so those checkpoints get distilled sampling defaults
(guidance 1.0 / 16 steps) instead of the sft fallback's 5.0 / 50.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Match the official kandinskylab/kandinsky-5 RNG order for I2V seed parity:
image encoding now runs after latent preparation and places the conditioning
latent itself, so the initial noise is the seeded generator's first draw
(upstream leaves the image-latent sample unseeded; drawing it second from the
same generator keeps FastVideo deterministic). The denoising stage now sets
the forward context with NABLA attention metadata per step — which also
routes the dense path through LocalAttention instead of the no-context SDPA
fallback. Resize tensor conditioning images to the requested resolution like
the PIL path. Collapse Kandinsky5DecodingStage to a channels-first permute +
super().forward(), regaining the base class's MPS handling.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
