Update app.py

app.py

@@ -10,15 +10,15 @@ tinier = AutoModelForCausalLM.from_pretrained("afrizalha/Sasando-1-7M", token=hf
 
 desc = """Sasando-1 is a tiny, highly experimental text generator built using the Phi-3 architecture. It comes with two variations of microscopic sizes: 7M and 25M parameters. It is trained on a tightly-controlled Indo4B dataset filtered to only have 18000 unique words. The method is inspired by Microsoft's TinyStories paper which demonstrates that a tiny language model can produce fluent text when trained on tightly-controlled dataset.\n\nTry prompting with two simple words, and let the model continue. Fun examples provided below."""
 
-def generate(starting_text, choice, temp, top_p):
+def generate(starting_text=None, choice=None, temp=None, top_p=None, info=False):
+    if info:
+        return desc
+    
     if choice == '7M':
         model = tinier
     elif choice == '25M':
         model = tiny
-    elif choice == 'Info':
-        yield desc
-        return
-
+    
     results = []
     for i in range(5):
         inputs = tokenizer([starting_text], return_tensors="pt").to(model.device)
@@ -32,23 +32,30 @@ def generate(starting_text, choice, temp, top_p):
         outputs = tokenizer.batch_decode(outputs, skip_special_tokens=True)[0]
         outputs = outputs[:outputs.find(".")]
         results.append(outputs)
-    yield "\n\n".join(results)
-    
+    return "\n\n".join(results)
+
 with gr.Blocks(theme=gr.themes.Soft()) as app:
     starting_text = gr.Textbox(label="Starting text", value="cinta adalah")
-    choice = gr.Radio(["7M", "25M", "Info"], label="Select model", info="Built with the Phi-3 architecture", value='Info')
-    # num_runs = gr.Slider(label="Number of examples", minimum=1, maximum=10, step=1, value=5)
-    temp = gr.Slider(label="Temperature", minimum=0.1, maximum=1.0, step=0.1, value=0.7)
-    top_p = gr.Slider(label="Top P", minimum=0.1, maximum=1.0, step=0.1, value=0.5)
+    choice = gr.Radio(["7M", "25M"], label="Select model", value="7M")
+    info_button = gr.Button("Info")
+    
+    with gr.Row():
+        temp = gr.Slider(label="Temperature", minimum=0.05, maximum=1.0, step=0.05, value=0.7)
+        top_p = gr.Slider(label="Top P", minimum=0.05, maximum=1.0, step=0.05, value=0.5)
+    
     res = gr.Textbox(label="Continuation")
+    
     gr.Interface(
         fn=generate,
-        inputs=[starting_text,choice,temp,top_p],
+        inputs=[starting_text, choice, temp, top_p, info_button],
         outputs=[res],
         allow_flagging="never",
         title="Sasando-1",
-        )
-    examples=gr.Examples([["gue"], ["presiden"], ["cinta adalah"], ["allah, aku"], ["dia marah karena"], 
-                          ["inflasi"], ["kolam renang"], ["messi"], ["jalan-jalan"], ["komputer itu"]], [starting_text])
+    )
+    
+    examples = gr.Examples([
+        ["gue"], ["presiden"], ["cinta adalah"], ["allah, aku"], ["dia marah karena"],
+        ["inflasi"], ["kolam renang"], ["messi"], ["jalan-jalan"], ["komputer itu"]
+    ], [starting_text])
 
 app.launch()