Update README.md

README.md

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 GLADOS-1 is the first computer-use (CUA) model post-trained using **collective, crowd-sourced trajectories**. 
 Leveraging the enourmous [Pango dataset](https://huggingface.co/datasets/chakra-labs/pango-sample) (with primarily Chrome based interactions), it's purpose is to provide a lense as to what's possible with enormous trajectory sizes in computer use.
 
-It also represents the first open-sourced post-training pipeline for [UI-TARS](https://arxiv.org/pdf/2501.12326, inspired by the existing [Qwen2VL finetuning series](https://github.com/2U1/Qwen2-VL-Finetune).
+It also represents the first open-sourced post-training pipeline for [UI-TARS](https://arxiv.org/pdf/2501.12326), inspired by the existing [Qwen2VL finetuning series](https://github.com/2U1/Qwen2-VL-Finetune).
 
 This model is designed to: 
 - **Be compliant**. It has been taught to rigorouly follow directions and output action formats compatible with downstream parsers like PyAutoGUI.