# Public inference contract for the generator-only release.
# This file intentionally does not reference the private training manifest.
algorithm:
  generator_is_causal: false

model_kwargs:
  model_name: Wan2.2-TI2V-5B
  timestep_shift: 5.0
  num_frame_per_block: 8
  local_attn_size: -1
  controlnet_model_path: TheDenk/wan2.2-ti2v-5b-controlnet-depth-v1
  controlnet_weight: 0.8
  controlnet_stride: 3

checkpoints:
  lora_ckpt: generator_lora.pt

inference:
  sampling_steps: 4
  guidance_scale: 1.0
  width: 832
  height: 480
  raw_frames: 93
  latent_frames: 24
  fps: 24
  control_guidance_start: 0.0
  control_guidance_end: 0.8
  sink_size: 0
  multi_shot_rope_offset: 0

adapter:
  type: lora
  rank: 64
  alpha: 64
  dropout: 0.0

notes:
  - The LoRA adapts the Wan transformer; it is not a ControlNet checkpoint.
  - The TheDenk depth ControlNet is a separate frozen runtime dependency.
  - Use a genuinely dynamic depth video; do not repeat one still depth map.
  - Other frame counts are temporal extrapolation from 93 raw / 24 latent frames.