cast float to int

text_classification.py

@@ -287,7 +287,9 @@ def get_example_prediction(model_id, dataset_id, dataset_config, dataset_split):
         results = hf_inference_api(model_id, hf_token, payload)
 
         if isinstance(results, dict) and "estimated_time" in results.keys():
-            return prediction_input, str(results["estimated_time"])
+            # return the estimated time for the inference api to load
+            # cast the float to int to be concise
+            return prediction_input, str(f"{int(results['estimated_time'])}s")
 
         if isinstance(results, dict) and "error" in results.keys():
             raise ValueError(results["error"])
@@ -300,7 +302,7 @@ def get_example_prediction(model_id, dataset_id, dataset_config, dataset_split):
             f'{result["label"]}': result["score"] for result in results
         }
     except Exception as e:
-        # Pipeline prediction failed, need to provide labels
+        # inference api prediction failed, show the error message
         return prediction_input, e
 
     return prediction_input, prediction_result

text_classification_ui_helpers.py

@@ -219,18 +219,18 @@ def align_columns_and_show_prediction(
             gr.update(visible=False),
             gr.update(visible=False, open=False),
             gr.update(interactive=False),
-            f"Hugging Face Inference API is loading your model, estimation time {prediction_response}",
+            f"Hugging Face Inference API is loading your model, estimation time {prediction_response}. Please validate again later.",
             *dropdown_placement,
         )
 
     if isinstance(prediction_response, Exception):
-        gr.Warning("Please check your model or Hugging Face token.")
+        gr.Warning("Inference API loading error: {prediction_response}. Please check your model or Hugging Face token.")
         return (
             gr.update(visible=False),
             gr.update(visible=False),
             gr.update(visible=False, open=False),
             gr.update(interactive=False),
-            f"Sorry, inference api loading error {prediction_response}, please check your model and token.",
+            "",
             *dropdown_placement,
         )