Make the dataset selector more visible

app.py

@@ -132,9 +132,6 @@ def generate_dataset_info(datasets):
             msg += f"* [{dataset_id}](https://hf.co/datasets/{dataset_id}) *(recommended)*\n"
         else:
             msg += f"* [{dataset_id}](https://hf.co/datasets/{dataset_id})\n"
-    msg += """
-    Choose the dataset that is most relevant to your task and select it from the dropdown below.
-    """
 
     msg = "\n".join([line.strip() for line in msg.split("\n")])
     return msg
@@ -162,9 +159,6 @@ lang_df = dataframe[dataframe.lang == lang]
 
 sorted_datasets = sort_datasets(lang_df["dataset"].unique())
 
-text = generate_dataset_info(sorted_datasets)
-st.sidebar.markdown(text)
-
 lang_name = lang2name[lang] if lang in lang2name else ""
 num_models = len(lang_df["model_id"].unique())
 num_datasets = len(lang_df["dataset"].unique())
@@ -174,6 +168,10 @@ trained on `{num_datasets}` dataset(s) available for `automatic-speech-recogniti
 """
 st.markdown(text)
 
+st.sidebar.markdown("""
+Choose the dataset that is most relevant to your task and select it from the dropdown below:
+""")
+
 dataset = st.sidebar.selectbox(
     "Dataset",
     sorted_datasets,
@@ -181,6 +179,9 @@ dataset = st.sidebar.selectbox(
 )
 dataset_df = lang_df[lang_df.dataset == dataset]
 
+text = generate_dataset_info(sorted_datasets)
+st.sidebar.markdown(text)
+
 # sort by WER or CER depending on the language
 metric_col = "cer" if lang in cer_langs else "wer"
 if dataset_df["config"].nunique() > 1: