update

app.py

@@ -16,9 +16,12 @@ def restart_space():
     )
 
 
-open_llm_race_dataset = pd.read_csv(
-    "https://huggingface.co/datasets/IlyasMoutawwakil/open-llm-race-dataset/resolve/main/open-llm-race-dataset.csv"
-)
+if os.path.exists("open-llm-race-dataset.csv"):
+    open_llm_race_dataset = pd.read_csv("open-llm-race-dataset.csv")
+else:
+    open_llm_race_dataset = pd.read_csv(
+        "https://huggingface.co/datasets/IlyasMoutawwakil/open-llm-race-dataset/resolve/main/open-llm-race-dataset.csv"
+    )
 
 
 # resample for ever model to a daily frequency
@@ -63,7 +66,7 @@ def get_bar_chart(model_type: str, top_n: int = 10):
         filter_column_colors=True,
         fig=fig,
     )
-    gr.HTML(fig.data)
+    return gr.HTML(fig)
 
 
 # Demo interface
@@ -73,10 +76,10 @@ with demo:
     gr.HTML("<center><h1>LLM Bar Race 📊🏃‍♂️</h1></center>")
 
     with gr.Tabs():
-        with gr.TabItem(label="Pretrained Models"):
-            get_bar_chart(ModelType.PT.name)
-        with gr.TabItem(label="Instructions Finetuend Models"):
-            get_bar_chart(ModelType.IFT.name)
+        # with gr.TabItem(label="Pretrained Models"):
+        #     get_bar_chart(ModelType.PT.name)
+        # with gr.TabItem(label="Instructions Finetuend Models"):
+        #     get_bar_chart(ModelType.IFT.name)
         with gr.TabItem(label="RLHF Models"):
             get_bar_chart(ModelType.RL.name, top_n=4)
 

requirements.txt

@@ -1,6 +1,5 @@
 git+https://github.com/dexplo/bar_chart_race.git
 huggingface_hub
 APScheduler
-ipython
 pandas
 tqdm