README.md

metadata

license: openrail

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.