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base_model: THUDM/CogVideoX-2b
library_name: peft
tags:
- lora
- dora
- cogvideox
- physics
- video-generation
- warp
---
# PDW — Physics-Corrected CogVideoX-2b World Model (DoRA Adapter)
A **DoRA (Weight-Decomposed Low-Rank Adaptation)** adapter for [CogVideoX-2b](https://huggingface.co/THUDM/CogVideoX-2b), fine-tuned to generate physically accurate videos using **NVIDIA Warp** physics simulation data and **TRD (Temporal Representation Distillation)** with DINOv2-large as teacher.
## Model Details
- **Base model:** THUDM/CogVideoX-2b (1.7B params)
- **Adapter:** DoRA (r=16, lora_alpha=32, use_dora=True)
- **Target modules:** `to_q`, `to_k`, `to_v`, `to_out.0`
- **Trainable params:** 7.6M / 1.7B (0.45%)
- **Physics engine:** NVIDIA Warp (28-scenario 7×4 grid)
- **TRD teacher:** DINOv2-large
- **Hardware:** NVIDIA H100 NVL
- **Training steps:** 400
## Evaluation Results
| Metric | Delta |
|---|---|
| Diffusion MSE | +94.1% |
| Motion score | +1.7% |
| Overall | +47.9% |
## How to Use
```python
from peft import PeftModel
from diffusers import CogVideoXTransformer3DModel
# Load base transformer
base_transformer = CogVideoXTransformer3DModel.from_pretrained(
"THUDM/CogVideoX-2b", subfolder="transformer"
)
# Load DoRA adapter
model = PeftModel.from_pretrained(base_transformer, "athul020/pdw_final_dora")
```
### Framework versions
- PEFT 0.18.1 |