Update app.py

app.py

@@ -11,7 +11,19 @@ MODEL_NAME = "atlasia/Al-Atlas-LLM"
 tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, token=token)
 model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, token=token)
 
-def generate_text(prompt, max_length=256, temperature=0.7, top_p=0.9, top_k=150, repetition_penalty=1.5):
+# Predefined examples
+examples = [
+    ["الذكاء الاصطناعي هو فرع من علوم الكمبيوتر اللي كيركز"
+     , 256, 0.7, 0.9, 150, 8, 1.5],
+    ["المستقبل ديال الذكاء الصناعي فالمغرب"
+     , 256, 0.7, 0.9, 150, 8, 1.5],
+    [" المطبخ المغربي"
+     , 256, 0.7, 0.9, 150, 8, 1.5],
+    ["الماكلة المغربية كتعتبر من أحسن الماكلات فالعالم"
+     , 256, 0.7, 0.9, 150, 8, 1.5],
+]
+
+def generate_text(prompt, max_length=256, temperature=0.7, top_p=0.9, top_k=150, num_beams=8, repetition_penalty=1.5):
     inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
     output = model.generate(
         **inputs, 
@@ -20,7 +32,7 @@ def generate_text(prompt, max_length=256, temperature=0.7, top_p=0.9, top_k=150,
         top_p=top_p, 
         do_sample=True,
         repetition_penalty=repetition_penalty,
-        num_beams=8,
+        num_beams=num_beams,
         top_k= top_k,
         early_stopping = True,
     )
@@ -35,12 +47,14 @@ iface = gr.Interface(
         gr.Slider(0.1, 1.5, value=0.7, label="Temperature"),
         gr.Slider(0.1, 1.0, value=0.9, label="Top-p"),
         gr.Slider(1, 10000, value=150, label="Top-k"),
+        gr.Slider(1, 20, value=8, label="Number of Beams"),
         gr.Slider(0.0, 100.0, value=1.5, label="Repetition Penalty"),
     ],
     outputs=gr.Textbox(label="Generated Text in Moroccan Darija"),
     title="Moroccan Darija LLM",
-    description="Enter a prompt and get AI-generated text using our pretrained LLM on Moroccan Darija."
+    description="Enter a prompt and get AI-generated text using our pretrained LLM on Moroccan Darija.",
+    examples=examples,
 )
 
 if __name__ == "__main__":
-    iface.launch()
+    iface.launch(share=True)