| This is the model repository of paper *EDGE: Enhanced Grounded GUI Understanding with Enriched Multi-Granularity Synthetic Data*. | |
| The model is fine-tuned based on [*Monkey*](https://github.com/Yuliang-Liu/Monkey). In order to speed up the training, we also made some minor modifications: | |
| 1. Instead of using the Lora Adapters in *Monkey*, the five patches of the raw image are stacked in an extra batch dimension and sent to the image encoder for processing at the same time. | |
| 2. Inside the image encoder, we use [*flash attention*](https://github.com/Dao-AILab/flash-attention) instead of the manually implemented attention. | |
| 3. Separate the step of reading the image from the forward propagation and make it a step of dataset preprocessing to speed up image reading using the `Dataloader` in pytorch. | |
| The training dataset (i.e. all training QAs in `.jsonl` format, excluding images) is published in repository [*EDGE-Dataset*](https://huggingface.co/datasets/EDGEwww25/EDGE-Dataset/settings). | |
| The model training and inference scripts are published in anonymous repository [*EDGE*](https://anonymous.4open.science/r/EDGE-1CDB). | |