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Safetensors

Micro-World 2.0

Action-controlled causal world-model checkpoints. Micro-World 2.0 generates 352×640 video from a first frame, a text prompt, and keyboard/mouse actions. The distilled student denoises each chunk in 4 steps.

The Wan2.2-TI2V-5B base weights are not in this repository; download them from Wan-AI/Wan2.2-TI2V-5B.

Checkpoints

Path What it is
causal-forcing-init/model.pt Causal-forcing initialization. Loaded onto the Wan2.2 transformer before the LoRAs.
causal-lora/lora_diffusion_pytorch_model.safetensors Causal LoRA. Adapts the backbone to open-domain 352×640 video.
action/ Action module. Inference reads action_preprocess and action_adaLN_modulation from this checkpoint.
dmd-lora/lora_diffusion_pytorch_model.safetensors DMD student LoRA used for 4-step generation.
light_vae/ Optional TurboVAED decoder from amd/HummingbirdXT. Faster decode with few loss of fidelity. Omit it to use the Wan VAE.

Load order

  1. Wan2.2-TI2V-5B transformer, VAE, and text encoder
  2. causal-forcing-init/model.pt
  3. causal-lora
  4. action
  5. dmd-lora

Training and inference code: Micro-World.

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