Update model names

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

@@ -12,4 +12,4 @@ OpenCLIP-FFT,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
-VLM2Vec (LLaVA-1.6-LoRA-HighRes),7.57,TIGER-Lab,62.9,67.5,57.1,61.2,49.9,67.4,86.1
+VLM2Vec (LLaVA-1.6-LoRA-HighRes),7.57,TIGER-Lab,62.9,67.5,57.1,61.2,49.9,67.4,86.1

utils.py

@@ -96,6 +96,27 @@ SUBMIT_INTRODUCTION = """# Submit on MMEB Leaderboard Introduction
 Please send us an email at m7su@uwaterloo.ca, 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"
@@ -105,6 +126,7 @@ def get_df():
         sys.exit(f"Error: {response.status_code}")
     df = pd.read_csv(io.StringIO(response.text))
     df.to_csv(CSV_DIR, index=False) # update local file
+    df = pd.read_csv(CSV_DIR)
     df['Model Size(B)'] = df['Model Size(B)'].apply(process_model_size)
     df = df.sort_values(by=['Overall'], ascending=False)
     return df