Update app.py

app.py

@@ -8,15 +8,15 @@ model = AutoModelForCausalLM.from_pretrained("unsloth/Llama-3.2-1B")
 # Use a pipeline for text generation
 text_gen_pipeline = pipeline("text-generation", model=model, tokenizer=tokenizer)
 
-# Text generation function with stronger penalties and no_repeat_ngram_size
-def generate_text(prompt, max_length=40, temperature=0.8, top_p=0.9, top_k=40, repetition_penalty=1.5, no_repeat_ngram_size=4):
+# Text generation function with repetition penalty and no_repeat_ngram_size
+def generate_text(prompt, max_length=50, temperature=0.7, top_p=0.9, top_k=50, repetition_penalty=1.2, no_repeat_ngram_size=3):
     generated_text = text_gen_pipeline(prompt, 
                                        max_length=max_length, 
                                        temperature=temperature, 
                                        top_p=top_p, 
                                        top_k=top_k, 
-                                       repetition_penalty=repetition_penalty,  # Stronger repetition penalty
-                                       no_repeat_ngram_size=no_repeat_ngram_size,  # Higher n-gram size to reduce repetition
+                                       repetition_penalty=repetition_penalty,  # Penalty to avoid repetitions
+                                       no_repeat_ngram_size=no_repeat_ngram_size,  # Avoid repeating n-grams
                                        num_return_sequences=1)
     return generated_text[0]['generated_text']
 
@@ -28,22 +28,22 @@ with gr.Blocks() as demo:
     prompt_input = gr.Textbox(label="Input (Prompt)", placeholder="Enter your prompt here...")
     
     # Slider for maximum text length
-    max_length_input = gr.Slider(minimum=10, maximum=200, value=40, step=10, label="Maximum Length")
+    max_length_input = gr.Slider(minimum=10, maximum=200, value=50, step=10, label="Maximum Length")
     
     # Slider for temperature (controls creativity)
-    temperature_input = gr.Slider(minimum=0.1, maximum=1.0, value=0.8, step=0.1, label="Temperature (creativity)")
+    temperature_input = gr.Slider(minimum=0.1, maximum=1.0, value=0.7, step=0.1, label="Temperature (creativity)")
     
     # Slider for top_p (nucleus sampling)
     top_p_input = gr.Slider(minimum=0.1, maximum=1.0, value=0.9, step=0.1, label="Top-p (nucleus sampling)")
     
     # Slider for top_k (controls diversity)
-    top_k_input = gr.Slider(minimum=1, maximum=100, value=40, step=1, label="Top-k (sampling diversity)")
+    top_k_input = gr.Slider(minimum=1, maximum=100, value=50, step=1, label="Top-k (sampling diversity)")
     
     # Slider for repetition penalty
-    repetition_penalty_input = gr.Slider(minimum=1.0, maximum=2.0, value=1.5, step=0.1, label="Repetition Penalty")
+    repetition_penalty_input = gr.Slider(minimum=1.0, maximum=2.0, value=1.2, step=0.1, label="Repetition Penalty")
     
     # Slider for no_repeat_ngram_size
-    no_repeat_ngram_size_input = gr.Slider(minimum=1, maximum=10, value=4, step=1, label="No Repeat N-Gram Size")
+    no_repeat_ngram_size_input = gr.Slider(minimum=1, maximum=10, value=3, step=1, label="No Repeat N-Gram Size")
     
     # Output box for the generated text
     output_text = gr.Textbox(label="Generated Text")