Update app.py

app.py

@@ -14,14 +14,14 @@ token = os.environ.get("HF_TOKEN")
 #tokenizer = AutoTokenizer.from_pretrained("openai-community/gpt2")
 #model = AutoModelForCausalLM.from_pretrained("openai-community/gpt2")
 
-tokenizer_gpt2 = AutoTokenizer.from_pretrained("openai-community/gpt2")
-model_gpt2 = AutoModelForCausalLM.from_pretrained("openai-community/gpt2")
+#tokenizer_gpt2 = AutoTokenizer.from_pretrained("openai-community/gpt2")
+#model_gpt2 = AutoModelForCausalLM.from_pretrained("openai-community/gpt2")
 
 #tokenizer_gemma = AutoTokenizer.from_pretrained("google/gemma-2b")
 #model_gemma = AutoModelForCausalLM.from_pretrained("google/gemma-2b", token=token)
 
-tokenizer_qwen = AutoTokenizer.from_pretrained("Qwen/Qwen2-0.5B")
-model_qwen = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-0.5B")
+#tokenizer_qwen = AutoTokenizer.from_pretrained("Qwen/Qwen2-0.5B")
+#model_qwen = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-0.5B")
 
 # Define functions
 
@@ -316,16 +316,17 @@ with gr.Blocks() as demo:
     
     No_beam_group_list = [2]
         
-    tokenizer = tokenizer_gpt2
-    model = model_gpt2
+    #tokenizer = tokenizer_gpt2
+    #model = model_gpt2
     
     with gr.Row():
         
         with gr.Column (scale=0, min_width=200) as Models_Strategy:
             
             model_selected = gr.Radio (["GPT2", "Qwen2"], label="ML Model", value="GPT2")
-            strategy_selected = gr.Radio (["Sampling", "Beam Search", "Diversity Beam Search","Contrastive"], label="Search strategy", value = "Sampling", interactive=True)
             load_model_button = gr.Button("Load")
+            strategy_selected = gr.Radio (["Sampling", "Beam Search", "Diversity Beam Search","Contrastive"], label="Search strategy", value = "Sampling", interactive=True)
+            
         
         with gr.Column(scale=1):