Update README.md

README.md

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-This dataset is combined and deduplicated version of (coco-2014)[https://huggingface.co/datasets/detection-datasets/coco] and (coco-2017)[https://huggingface.co/datasets/rafaelpadilla/coco2017] datasets for object detection. The labels are in Turkish and the dataset is in an instruction-tuning format with separate columns for prompts and completion labels. 
+This dataset is combined and deduplicated version of [coco-2014](https://huggingface.co/datasets/detection-datasets/coco) and [coco-2017](https://huggingface.co/datasets/rafaelpadilla/coco2017) datasets for object detection. The labels are in Turkish and the dataset is in an instruction-tuning format with separate columns for prompts and completion labels. 
 
-For the bounding boxes, a similar annotation scheme to that of (PaliGemma)[https://huggingface.co/blog/paligemma#Detection] annotation is used. That is, 
+For the bounding boxes, a similar annotation scheme to that of [PaliGemma](https://huggingface.co/blog/paligemma#Detection) annotation is used. That is, 
 ```
 The bounding box coordinates are in the form of special <loc[value]> tokens, where value is a number that represents a normalized coordinate. Each detection is represented by four location coordinates in the order x_min(left), y_min(top), x_max(right), y_max(bottom), followed by the label that was detected in that box. To convert values to coordinates, you first need to divide the numbers by 1024, then multiply y by the image height and x by its width. This will give you the coordinates of the bounding boxes, relative to the original image size.
 ```