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hao-ai-lab-FastVideo/examples/train/scenario/worldmodel
d6dfe95466 [feat] FastVideo World Model Training (#1179)
Co-authored-by: mignonjia <mhuo@ucsd.edu>
Co-authored-by: alexzms <3036648523@qq.com>
Co-authored-by: mergify[bot] <37929162+mergify[bot]@users.noreply.github.com>
2026-05-11 05:13:12 +00:00
..

World-Model: MatrixGame 2.0 I2V

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

Config Method Student Notes
finetune_i2v.yaml FineTuneMethod MatrixGameModel (bidirectional) Multi-step SFT from mg_bidirectional_Solaris.
dfsft_causal_i2v.yaml DiffusionForcingSFTMethod MatrixGameCausalModel Diffusion-Forcing SFT with chunkwise timesteps.
self_forcing_causal_i2v.yaml SelfForcingMethod MatrixGameCausalModel 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