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| Size | 2B |
| Stage | Post-training |
| Architecture | DiT (Diffusion Transformer) with AdaLN-LoRA |
| Base | Cosmos Predict 2.5 |
DreamDojo-YAM-2B-Diffusers/
├── transformer/ # DiT backbone (sharded safetensors)
├── crossattn_adapter/ # Text-to-DiT projection (100352 → 1024)
├── vae/ # AutoencoderKLWan (standard diffusers)
├── lam/ # Latent Action Model (710M params)
├── text_encoder/ # Cosmos-Reason1-7B
├── scheduler/ # FlowMatchEulerDiscreteScheduler
├── action_processor/ # DreamDojo-specific config
└── config.json| 2B | |
|---|---|
| Model channels | 2048 |
| Transformer blocks | 28 |
| Attention heads | 16 |
| Patch size (spatial / temporal) | 2 / 1 |
| Action dim | 384 (unified) |
1@article{dreamdojo2025,
2 title={DreamDojo: Advancing Real-World Robot Policies Through Generated Interactive Environments},
3 author={NVIDIA},
4 year={2025}
5}