README.md

metadata

title: Streaming Code World Model
emoji: 🌍
colorFrom: blue
colorTo: red
sdk: gradio
sdk_version: 6.30.0
app_file: app.py
short_description: Causal chunk-by-chunk world-model video streaming
python_version: '3.12'
startup_duration_timeout: 1h
models:
  - Luffuly/streaming-code-world-model
  - Comfy-Org/MiniMax-H3

Streaming Code World Model

Demo of Streaming Code World Model (checkpoints): causal, chunk-by-chunk video generation from a live control proxy, built on Code World Model (MiniMax-H3 Ref2VA + CWM LoRA).

Sampling follows rtcwm.eval.open_world generate --steps 4 --rule x0 --shift 5 --kv-reuse --fp8 with streaming_dmd_4step.safetensors. Adaptations for ZeroGPU (RTX PRO 6000 Blackwell): FlashAttention-3 / flex-attention replaced by PyTorch SDPA over the same block-causal key prefixes, FP8 block linears (the authors' --fp8), and the per-block AdaLN projections precomputed for the sampler's fixed set of timesteps.

Scenes are released Code World Model inference examples (NTU-yiwen/code-world-model-inference-examples-40): their start frame, the "Appearance and scene" caption of the first window and the Depth + Semantic-ID proxy, pre-encoded (Qwen3-VL-32B states, VAE latents) exactly as rtcwm.eval.open_world prepare does.

Vendored code: musubi_tuner/ (kohya-ss/musubi-tuner @ c4dc6b8 + the CWM minimax-h3-retake34 and headless patches, Apache-2.0), cwm_h3_inference/ (buaacyw/code-world-model, Apache-2.0), rtcwm/ (TingtingLiao/streaming-code-world-model).