Update app.py

app.py

@@ -7,19 +7,21 @@ def generate_story(title, model_name):
     generator = pipeline('text-generation', model=model_name)
     # Generate the story based on the input title
     story = generator(title,
-                      max_length=200,  # Fixed max length for the story
-                      temperature=0.7, # Fixed temperature for some randomness
-                      num_return_sequences=1)
-
+                      max_length=230,  # Set the maximum length for the generated text (story) to 230 tokens
+                      no_repeat_ngram_size=3,  # Avoid repeating any sequence of 3 words (to prevent repetitive text)
+                      temperature=0.8,  # Introduce some randomness; higher values make the output more random, lower makes it more deterministic
+                      top_p=0.95  # Use nucleus sampling (top-p sampling) to focus on the top 95% of probable words, making the text more coherent
+                      )
     # Return the generated text
     return story[0]['generated_text']
-    
+
 # Create the Gradio interface using gr.Interface
 demo = gr.Interface(
     fn=generate_story,  # The function to run
     inputs=[             # Inputs for the interface
         gr.Textbox(label="Enter Story Title", placeholder="Type a title here..."),  # Title input
-        gr.Dropdown(choices=['gpt2', 'gpt2-medium', 'gpt2-large', 'EleutherAI/gpt-neo-2.7B', 'EleutherAI/gpt-j-6B','maldv/badger-writer-llama-3-8b'],
+        gr.Dropdown(choices=['gpt2', 'gpt2-large', 'EleutherAI/gpt-neo-2.7B', 'EleutherAI/gpt-j-6B',
+                             'maldv/badger-writer-llama-3-8b', 'EleutherAI/gpt-neo-1.3B'],
                     value='gpt2',
                     label="Choose Model")  # Model selection input
     ],