Add pipeline tag, library name, and paper link

README.md

@@ -1,6 +1,9 @@
 ---
 license: mit
+library_name: transformers
+pipeline_tag: image-to-text
 ---
+
 <h2>[Installation Free!] Quicker Start with Hugging Face AutoModel</h2> 
 
 No need to install this GitHub repo. Ensure that you use the Transformers package of 4.45.0 (`pip install transformers==4.45.0`).
@@ -77,7 +80,9 @@ conversation = [
     {
         "role": "user",
         "content": [
-            {"type": "text", "text": "Assume you are an image quality evaluator. \nYour rating should be chosen from the following five categories: Excellent, Good, Fair, Poor, and Bad (from high to low). \nHow would you rate the quality of this image?"},
+            {"type": "text", "text": "Assume you are an image quality evaluator. 
+Your rating should be chosen from the following five categories: Excellent, Good, Fair, Poor, and Bad (from high to low). 
+How would you rate the quality of this image?"},
             {"type": "image"},
         ],
     },
@@ -112,3 +117,5 @@ print("Weighted average score:", weighted_score)
 ```
 
 To test q-sit on datasets, please refer to evaluation scripts [here](https://github.com/Q-Future/Q-SiT/tree/main/eval_scripts).
+
+This model is described in [](https://huggingface.co/papers/2503.09197). The code is available at https://github.com/Q-Future/Q-SiT.