Update README.md

README.md

@@ -160,7 +160,7 @@ The annotation data is stored in
 
 ### Best practice
 
-During the training of **OS-Atlas-7B**, we randomly sampled predefined prompts to wrap the grounding data. Additionally, we scaled the relative coordinates of each element (in the range [0, 1]) by multiplying them by 1000 before inputting them into the model for training. 
+During the training of **OS-Atlas-4B**, we randomly sampled predefined prompts to wrap the grounding data. Additionally, we scaled the relative coordinates of each element (in the range [0, 1]) by multiplying them by 1000 before inputting them into the model for training. 
 
 Below is an example of a data entry:
 
@@ -179,6 +179,23 @@ Below is an example of a data entry:
 }
 ```
 
+**OS-Atlas-7B**
+
+```
+{
+  "conversations": [
+    {
+      "from": "human",
+      "value": "<image>\nUsing the provided screenshot, I'll describe webpage elements for you to locate (with bbox).\n<|object_ref_start|>Facebook<|object_ref_end|>\n<|object_ref_start|>Subscribe<|object_ref_end|>\n<|object_ref_start|>Twitter<|object_ref_end|>\n<|object_ref_start|>Read More<|object_ref_end|>\n<|object_ref_start|>Read More<|object_ref_end|>"
+    },
+    {
+      "from": "gpt",
+      "value": "<|object_ref_start|>Facebook<|object_ref_end|><|box_start|>(4,955),(36,970)<|box_end|>\n<|object_ref_start|>Subscribe<|object_ref_end|><|box_start|>(4,913),(43,932)<|box_end|>\n<|object_ref_start|>Twitter<|object_ref_end|><|box_start|>(39,955),(62,970)<|box_end|>\n<|object_ref_start|>Read More<|object_ref_end|><|box_start|>(30,138),(73,157)<|box_end|>\n<|object_ref_start|>Read More<|object_ref_end|><|box_start|>(30,139),(73,155)<|box_end|>"
+    }
+  ]
+}
+```
+
 The prompts we used are stored in `prompts.json`.
 
 ***