Files
hao-ai-lab-FastVideo/examples/train/scenario/worldmodel

World-Model: Matrix-Game 2.0 I2V

Three training scenarios for the Matrix-Game 2.0 I2V world model on the new YAML-driven trainer (fastvideo/train/entrypoint/train.py).

Config Method Student Notes
finetune_i2v.yaml FineTuneMethod MatrixGame2Model (bidirectional) Multi-step SFT from mg_bidirectional_Solaris.
dfsft_causal_i2v.yaml DiffusionForcingSFTMethod MatrixGame2CausalModel Diffusion-Forcing SFT with chunkwise timesteps.
self_forcing_causal_i2v.yaml SelfForcingMethod MatrixGame2CausalModel DMD/Self-Forcing distillation; teacher = bidirectional, critic = bidirectional.

Usage

bash examples/train/run.sh \
    examples/train/scenario/worldmodel/finetune_i2v.yaml

bash examples/train/run.sh \
    examples/train/scenario/worldmodel/dfsft_causal_i2v.yaml

bash examples/train/run.sh \
    examples/train/scenario/worldmodel/self_forcing_causal_i2v.yaml

Override any field on the command line:

bash examples/train/run.sh \
    examples/train/scenario/worldmodel/dfsft_causal_i2v.yaml \
    --training.distributed.num_gpus 8 \
    --training.optimizer.learning_rate 1e-5