Wrap column headers

app.py

@@ -163,10 +163,10 @@ def _prediction_loop(
             cache=CACHE,
         ).with_format("numpy")["__prediction__"].flatten()
         print(prediction)
-        this_col = f"{species}: predicted MIC (µM)"
+        this_col = f"{species}:\npredicted MIC (µM)"
         df[this_col] = np.power(10., -prediction) * 1e6
         prediction_cols.append(this_col)
-        this_col = f"{species}: predicted MIC (µg / mL)"
+        this_col = f"{species}:\npredicted MIC (µg / mL)"
         df[this_col] = np.power(10., -prediction) * 1e3 * df["mwt"]
         prediction_cols.append(this_col)
 
@@ -175,7 +175,7 @@ def _prediction_loop(
             print_err(message)
             gr.Info(message, duration=10)
             # this_modelbox._input_training_data = this_modelbox._input_training_data.remove_columns([this_modelbox._in_key])
-            this_col = f"{species}: {extra_metric}"
+            this_col = f"{species}:\n{extra_metric}"
             prediction_cols.append(this_col)
             print(">>>", this_modelbox._input_training_data)
             print(">>>", this_modelbox._input_training_data.format)
@@ -513,7 +513,6 @@ def _initial_setup():
     output_line = gr.DataFrame(
         label="Predictions (scroll left and right)",
         interactive=False,
-        max_chars=75,
         pinned_columns=3,
         visible=True,
     )