diff --git a/eval_scripts/mplug_owl_2/eval_image_quality.py b/eval_scripts/mplug_owl_2/eval_image_quality.py
index 124c109..8da2f62 100644
--- a/eval_scripts/mplug_owl_2/eval_image_quality.py
+++ b/eval_scripts/mplug_owl_2/eval_image_quality.py
@@ -51,22 +51,22 @@ def main(args):
 
     
     image_paths = [
+        "../datasets/LIVEC/Images/",
         "../datasets/AGIQA-3K/database/",
         "../datasets/1024x768/",
         "../datasets/SPAQ/",
         "../datasets/FLIVE_Database/database/",
-        "../datasets/LIVEC/Images/",
         "../datasets/CGIQA-6K/database/",
         "../datasets/kadid10k/images/",
     ]
 
     json_prefix = "../datasets/json/"
     jsons = [
+        json_prefix + "livec.json",
         json_prefix + "agi.json",
         json_prefix + "koniq.json",
         json_prefix + "spaq.json",
         json_prefix + "flive.json",
-        json_prefix + "livec.json",
         json_prefix + "cgi.json",
         json_prefix + "kadid.json",
     ]
diff --git a/eval_scripts/mplug_owl_2/eval_video_quality.py b/eval_scripts/mplug_owl_2/eval_video_quality.py
index 32f5619..aa3ac25 100644
--- a/eval_scripts/mplug_owl_2/eval_video_quality.py
+++ b/eval_scripts/mplug_owl_2/eval_video_quality.py
@@ -96,7 +96,7 @@ def main(args):
             images = load_video(image_path + filename)
             llddata["logit_good"] = 0
             llddata["logit_poor"] = 0
-
+            
             for image in images:
                 image_tensor = image_processor.preprocess(image, return_tensors='pt')['pixel_values'].half().cuda()
 
diff --git a/model_zoo/README.md b/model_zoo/README.md
index 910a41c..27c271c 100644
--- a/model_zoo/README.md
+++ b/model_zoo/README.md
@@ -21,7 +21,7 @@ If your server is facing poor connection to Huggingface, we provide an alternati
 #### Step 1: Download Weights
 
 
-The links are as follows (WIP):
+The links are as follows:
 
 
 _Released_:
@@ -29,18 +29,15 @@ _Released_:
 - [LLaVA-v1.5-7B (mix)](https://www.modelscope.cn/models/qfuture/llava_v1.5_7b_qinstruct_preview_v0.1), ModelScope-path: `qfuture/llava_v1.5_7b_qinstruct_preview_v0.1`
 - [LLaVA-v1.5-13B (mix)](https://www.modelscope.cn/models/qfuture/llava_v1.5_13b_qinstruct_preview_v0.1), ModelScope-path: `qfuture/llava_v1.5_13b_qinstruct_preview_v0.1`
 - [mPLUG-Owl-2 (mix)](https://www.modelscope.cn/models/qfuture/mplug_owl_2_qinstruct_preview_v0.1), ModelScope-path: `qfuture/mplug_owl_2_qinstruct_preview_v0.1`
-
-
-_Coming Soon_:
-
-- InternLM-XComposer-VL (mix)
+- [InternLM-XComposer-VL (mix)](https://www.modelscope.cn/models/qfuture/internlm_xcomposer_vl_qinstruct_preview_v0.1), ModelScope-path: `qfuture/internlm_xcomposer_vl_qinstruct_preview_v0.1`
 
 To use them, you need to install `Git LFS` and then clone the repositories directly from ModelScope, under the main directory of Q-Instruct.
 
 ```shell
-git clone https://www.modelscope.cn/models/qfuture/$MODEL_NAME_qinstruct_preview_v0.1.git
+git clone https://www.modelscope.cn/qfuture/$MODEL_NAME_qinstruct_preview_v0.1.git
 ```
 
+
 #### Step 2: Redirect the Model Paths to Your Local Directory
 
 After that, modify the `model_path` in [quick start](../README.md#quick-start) to the local path (i.e. `$MODEL_NAME_qinstruct_preview_v0.1`) to smoothly load the weights downloaded from ModelScope.