smoke test showed previous MC model performed better, commenting out 1on1

app.py

@@ -12,13 +12,13 @@ np.set_printoptions(suppress=True)
 
 def ai_generated_test(option, input):
     if option == "Human vs AI":
-        return predict_bc_scores(input), None, None
+        return predict_bc_scores(input), None
     elif option == "Human vs AI Source Models":
-        return (predict_bc_scores(input), predict_mc_scores(input), None)
-    elif option == "Human vs AI Source Models (1 on 1)":
-        return predict_bc_scores(input), None, predict_1on1_scores(input)
+        return predict_bc_scores(input), predict_mc_scores(input)
+    # elif option == "Human vs AI Source Models (1 on 1)":
+    #     return predict_bc_scores(input), None, predict_1on1_scores(input)
 
-    return None, None, None
+    return None, None
 
 
 # COMBINED
@@ -111,7 +111,7 @@ with gr.Blocks() as demo:
                 [
                     "Human vs AI",
                     "Human vs AI Source Models",
-                    "Human vs AI Source Models (1 on 1)",
+                    # "Human vs AI Source Models (1 on 1)",
                 ],
                 label="Choose an option please.",
             )
@@ -154,8 +154,8 @@ with gr.Blocks() as demo:
             bcLabel = gr.Label(label="Source")
         with gr.Column():
             mcLabel = gr.Label(label="Creator")
-        with gr.Column():
-            mc1on1Label = gr.Label(label="Creator(1 on 1 Approach)")
+        # with gr.Column():
+        #     mc1on1Label = gr.Label(label="Creator(1 on 1 Approach)")
     with gr.Row():
         QLabel = gr.Label(label="Humanized")
     with gr.Group():
@@ -222,7 +222,7 @@ with gr.Blocks() as demo:
         outputs=[
             bcLabel,
             mcLabel,
-            mc1on1Label,
+            # mc1on1Label,
             sentenceBreakdown,
             writing_analysis_plot,
             QLabel,
@@ -233,7 +233,8 @@ with gr.Blocks() as demo:
     only_ai_btn.click(
         fn=ai_generated_test,
         inputs=[ai_option, input_text],
-        outputs=[bcLabel, mcLabel, mc1on1Label],
+        # outputs=[bcLabel, mcLabel, mc1on1Label],
+        outputs=[bcLabel, mcLabel],
         api_name="ai_check",
     )
 

predictors.py

@@ -46,13 +46,13 @@ quillbot_tokenizer = AutoTokenizer.from_pretrained(text_quillbot_model_path)
 quillbot_model = AutoModelForSequenceClassification.from_pretrained(
     text_quillbot_model_path
 ).to(device)
-tokenizers_1on1 = {}
-models_1on1 = {}
-for model in text_1on1_models:
-    tokenizers_1on1[model] = AutoTokenizer.from_pretrained(model)
-    models_1on1[model] = AutoModelForSequenceClassification.from_pretrained(
-        model
-    ).to(device)
+# tokenizers_1on1 = {}
+# models_1on1 = {}
+# for model in text_1on1_models:
+#     tokenizers_1on1[model] = AutoTokenizer.from_pretrained(model)
+#     models_1on1[model] = AutoModelForSequenceClassification.from_pretrained(
+#         model
+#     ).to(device)
 
 
 def split_text_allow_complete_sentences_nltk(