Update README.md

README.md

@@ -16,7 +16,7 @@ tags:
 ## Model Description
 
 
-Ui-Taris-7B-Instruct-Finetuned-Os-Atlas is a GUI grounding model finetuned from [**UI-TARS-7B-DPO**](https://huggingface.co/bytedance-research/UI-TARS-7B-DPO).
+Ui-Tars-7B-Instruct-Finetuned-Os-Atlas is a GUI grounding model finetuned from [**UI-TARS-7B-DPO**](https://huggingface.co/bytedance-research/UI-TARS-7B-DPO).
 
 This model used the OS-Copilot dataset for fine-tuning: [OS-Copilot](https://huggingface.co/datasets/OS-Copilot/OS-Atlas-data/tree/main).
 
@@ -30,7 +30,7 @@ We also include evaluation scripts used on these benchmarks. The table below com
 |-------|:----:|:--------------:|:----------:|
 | [UI-TARS-7B-DPO](https://huggingface.co/bytedance-research/UI-TARS-7B-DPO) | 7B | 27.0 | 83.0 |
 | **Ours** | | | |
-| **Ui-Taris-7B-Instruct-Finetuned-Os-Atlas** | 7B | **33.0** | **91.8** |
+| **Ui-Tars-7B-Instruct-Finetuned-Os-Atlas** | 7B | **33.0** | **91.8** |
 
 **Note - The base model scores slightly lower than the mentioned scores in the paper because the prompts used for evaluation are not publicly available. We used the default prompts when evaluating the base and fine-tuned models.**
 
@@ -42,7 +42,7 @@ This model was trained with SFT and LoRA.
 
 ### Evaluation Scripts:
 
-Evaluation scripts available here - [Screenspot_Ui-Taris](https://github.com/ma-neuralleap/ScreenSpot-Pro-GUI-Grounding/blob/main/models/uitaris.py)
+Evaluation scripts available here - [Screenspot_Ui-Tars](https://github.com/ma-neuralleap/ScreenSpot-Pro-GUI-Grounding/blob/main/models/uitaris.py)
 
 ### Quick Start
 ```python
@@ -50,13 +50,13 @@ from transformers import Qwen2VLForConditionalGeneration, AutoTokenizer, AutoPro
 from qwen_vl_utils import process_vision_info
 # default: Load the model on the available device(s)
 model = Qwen2VLForConditionalGeneration.from_pretrained(
-    "Fintor/Ui-Taris-7B-Instruct-Finetuned-Os-Atlas", 
+    "Fintor/Ui-Tars-7B-Instruct-Finetuned-Os-Atlas", 
     torch_dtype=torch.bfloat16,
     attn_implementation="flash_attention_2",
     device_map="auto",
 )
 # default processer
-processor = AutoProcessor.from_pretrained("Fintor/Ui-Taris-7B-Instruct-Finetuned-Os-Atlas")
+processor = AutoProcessor.from_pretrained("Fintor/Ui-Tars-7B-Instruct-Finetuned-Os-Atlas")
 # Example input
 messages = [
     {