update model name and hyperlink

app.py

@@ -61,13 +61,14 @@ with gr.Blocks() as block:
                     elem_id="tasks-select"
                 )
 
+            print(create_hyperlinked_names(df)[COLUMN_NAMES])
             data_component = gr.components.Dataframe(
-                value=df[COLUMN_NAMES],
+                value=create_hyperlinked_names(df)[COLUMN_NAMES],
                 headers=COLUMN_NAMES,
                 type="pandas",
                 datatype=DATA_TITLE_TYPE,
                 interactive=False,
-                visible=True,
+                visible=True
             )
             
             refresh_button = gr.Button("Refresh")

results.csv

@@ -1,14 +1,14 @@
 Models,Model Size(B),Data Source,Overall,IND,OOD,Classification,VQA,Retrieval,Grounding
-CLIP,0.428,TIGER-Lab,37.8,37.1,38.7,42.8,9.1,53.0,51.8
-BLIP2,3.74,TIGER-Lab,25.2,25.3,25.1,27.0,4.2,33.9,47.0
-SigLIP,0.203,TIGER-Lab,34.8,32.3,38.0,40.3,8.4,31.6,59.5
-OpenCLIP,0.632,TIGER-Lab,39.7,39.3,40.2,47.8,10.9,52.3,53.3
+clip-vit-large-patch14,0.428,TIGER-Lab,37.8,37.1,38.7,42.8,9.1,53.0,51.8
+blip2-opt-2.7b,3.74,TIGER-Lab,25.2,25.3,25.1,27.0,4.2,33.9,47.0
+siglip-base-patch16-224,0.203,TIGER-Lab,34.8,32.3,38.0,40.3,8.4,31.6,59.5
+CLIP-ViT-H-14-laion2B-s32B-b79K,0.986,TIGER-Lab,39.7,39.3,40.2,47.8,10.9,52.3,53.3
 UniIR (BLIP_FF),0.247,TIGER-Lab,42.8,44.7,40.4,42.1,15.0,60.1,62.2
 UniIR (CLIP_SF),0.428,TIGER-Lab,44.7,47.1,41.7,44.3,16.2,61.8,65.3
-E5-V,8.36,TIGER-Lab,13.3,14.9,11.5,21.8,4.9,11.5,19.0
+e5-v,8.36,TIGER-Lab,13.3,14.9,11.5,21.8,4.9,11.5,19.0
 Magiclens,0.428,TIGER-Lab,27.8,31.0,23.7,38.8,8.3,35.4,26.0
-CLIP-FFT,0.428,TIGER-Lab,45.4,47.6,42.8,55.2,19.7,53.2,62.2
-OpenCLIP-FFT,0.632,TIGER-Lab,47.2,50.5,43.1,56.0,21.9,55.4,64.1
+CLIP-FullFineTuned,0.428,TIGER-Lab,45.4,47.6,42.8,55.2,19.7,53.2,62.2
+OpenCLIP-FullFineTuned,0.632,TIGER-Lab,47.2,50.5,43.1,56.0,21.9,55.4,64.1
 VLM2Vec (Phi-3.5-V-FFT),4.15,TIGER-Lab,55.9,62.8,47.4,52.8,50.3,57.8,72.3
 VLM2Vec (Phi-3.5-V-LoRA),4.15,TIGER-Lab,60.1,66.5,52.0,54.8,54.9,62.3,79.5
 VLM2Vec (LLaVA-1.6-LoRA-LowRes),7.57,TIGER-Lab,55.0,61.0,47.5,54.7,50.3,56.2,64.0

utils.py

@@ -96,6 +96,27 @@ SUBMIT_INTRODUCTION = """# Submit on MMEB Leaderboard Introduction
 Please send us an email at [email protected], attaching the JSON file. We will review your submission and update the leaderboard accordingly.
 """
 
+MODEL_URLS = {
+    "clip-vit-large-patch14": "https://huggingface.co/openai/clip-vit-large-patch14", 
+    "blip2-opt-2.7b": "https://huggingface.co/Salesforce/blip2-opt-2.7b",
+    "siglip-base-patch16-224": "https://huggingface.co/google/siglip-base-patch16-224", 
+    "CLIP-ViT-H-14-laion2B-s32B-b79K": "https://huggingface.co/laion/CLIP-ViT-H-14-laion2B-s32B-b79K", 
+    "e5-v": "https://huggingface.co/royokong/e5-v", 
+    "MagicLens": "https://github.com/google-deepmind/magiclens",
+
+}
+
+def create_hyperlinked_names(df):
+    def add_link_to_model_name(model_name):
+        if model_name in MODEL_URLS:
+            return f"<a href='{MODEL_URLS[model_name]}'>{model_name}</a>"
+        else:
+            return model_name
+    
+    df = df.copy()
+    df['Models'] = df['Models'].apply(add_link_to_model_name)
+    return df
+
 def get_df():
     # fetch the leaderboard data
     url = "https://huggingface.co/spaces/TIGER-Lab/MMEB/resolve/main/results.csv"