license: apache-2.0
language:
- en
base_model: MiniMaxAI/MiniMax-H3
base_model_relation: adapter
datasets:
- iapple1/CoCode-World-Data
pipeline_tag: image-to-video
tags:
- lora
- minimax-h3
- video-generation
- multi-view
- world-model
CoCode-World
Shared 3D Proxy Representation for Multi-Player World Models
Project Page 路 Code 路 Dataset 路 Examples
Model overview
CoCode-World generates synchronized video from two player perspectives using a shared 3D proxy representation. A reference image defines the visual appearance, a proxy video provides scene structure and motion, and a text prompt describes the scene.
This repository provides the official CoCode-World LoRA checkpoint for MiniMax-H3 Ref2VA. The recommended EMA weights are used in the released evaluation examples.
| Property | Description |
|---|---|
| Base model | MiniMax-H3 Ref2VA |
| Adapter | Rank-64 LoRA |
| Checkpoint | Step 4000 |
| Inputs | Reference image, synchronized proxy video, and text prompt |
| Output | Two player views arranged side by side |
| Resolution | 2560 脳 720 at 24 FPS |
Download
pip install -U huggingface_hub
hf download iapple1/CoCode-World-Model --local-dir checkpoints/step-004000
The repository includes ema.safetensors for inference, lora.safetensors for the task adapter, and training state and configuration files. Use the checkpoint loader in the official code repository. Download the MiniMax-H3 base model separately.
Usage
Follow the installation guide, then download the required models from the code repository:
python scripts/download_models.py base
python scripts/download_models.py cocode
The evaluation guide explains input preparation and generation. Eight ready-to-use examples include reference images, prompts, proxy videos, and generated results.
Training
Training starts from the official MiniMax-H3 weights and DiffSynth-Studio's Ref2VA DeCFG LoRA. The DeCFG adapter is used as a frozen training preset, followed by training a separate CoCode-World task LoRA. Inference uses the original MiniMax-H3 base and the CoCode-World EMA LoRA.
Training code and instructions are available in the training guide. The public dataset is a selected subset of the original training collection.
Intended use and limitations
The model supports research on multi-player world models, synchronized multi-view generation, and proxy-conditioned video synthesis. The first-frame reference guides appearance. Generated videos may contain visual artifacts or temporal inconsistencies, and the selected examples do not constitute a quantitative benchmark.
License and acknowledgments
The task adapter is released under Apache 2.0. The MiniMax-H3 base model is governed by the MiniMax-H3 Community License Agreement. The DeCFG training adapter retains its upstream terms.
CoCode-World builds on MiniMax-H3, DiffSynth-Studio, Diffusers, and Code World Model.