README.md

---
language:
  - en
license: mit
base_model: xlangai/OpenCUA-7B
tags:
  - world-model
  - computer-use
  - transition-prediction
  - lora
  - peft
library_name: peft
---

# World Model LoRA Adapter

LoRA adapter fine-tuned on [ageppert/world-model-transitions](https://huggingface.co/datasets/ageppert/world-model-transitions)
for predicting GUI state transitions in desktop computer-use tasks.

## Base Model
[xlangai/OpenCUA-7B](https://huggingface.co/xlangai/OpenCUA-7B)

## Usage
```python
from peft import PeftModel
from transformers import AutoModelForVision2Seq, AutoProcessor

base_model = AutoModelForVision2Seq.from_pretrained("xlangai/OpenCUA-7B", trust_remote_code=True)
model = PeftModel.from_pretrained(base_model, "ageppert/world-model-7b-lora")
processor = AutoProcessor.from_pretrained("ageppert/world-model-7b-lora")
```

## Training
- LoRA rank: 16, alpha: 32
- Target modules: ['q_proj', 'k_proj', 'v_proj', 'o_proj']
- Learning rate: 0.0002
- Epochs: 3
- Train loss: 4.954768469485616
- Eval loss: 0.5774359703063965

## Citation
Based on OpenCUA ([arXiv:2508.09123](https://arxiv.org/abs/2508.09123)).