New version with top_p, no examples to choose from and article text below the App.

app.py

@@ -5,7 +5,7 @@ import gradio as gr
 # Available models for pipeline
 # checkpoint = 'wvangils/CTRL-Beatles-Lyrics-finetuned-newlyrics'
 checkpoint = 'wvangils/GPT-Medium-Beatles-Lyrics-finetuned-newlyrics'
-# checkpoint = 'wvangils/GPT-Neo-125m-Beatles-Lyrics-finetuned-newlyrics'
+#checkpoint = 'wvangils/GPT-Neo-125m-Beatles-Lyrics-finetuned-newlyrics'
 # checkpoint = 'wvangils/GPT2-Beatles-Lyrics-finetuned-newlyrics'
 # checkpoint = 'wvangils/DistilGPT2-Beatles-Lyrics-finetuned-newlyrics'
 
@@ -13,7 +13,7 @@ checkpoint = 'wvangils/GPT-Medium-Beatles-Lyrics-finetuned-newlyrics'
 generator = pipeline("text-generation", model=checkpoint)
 
 # Create function for generation
-def generate_beatles(input_prompt, temperature):
+def generate_beatles(input_prompt, temperature, top_p):
     generated_lyrics = generator(input_prompt
                               , max_length = 100
                               , num_return_sequences = 1
@@ -23,7 +23,7 @@ def generate_beatles(input_prompt, temperature):
                               #, early_stopping = True    # Werkt niet goed lijkt 
                               , temperature = temperature    # Default 1.0    # Randomness, temperature = 1 minst risicovol, 0 meest risicovol
                               #, top_k = 50     # Default 50
-                              , top_p = 0.5    # Default 1.0
+                              , top_p = top_p    # Default 1.0
                               , no_repeat_ngram_size = 3   # Default = 0
                               , repetition_penalty = 1.0   # Default = 1.0
                               #, do_sample = True     # Default = False
@@ -31,18 +31,35 @@ def generate_beatles(input_prompt, temperature):
     return generated_lyrics
 
 # Create textboxes for input and output
-input_box = gr.Textbox(label="Input prompt:", placeholder="Write the start of a song here", lines=2)
-output_box = gr.Textbox(label="Lyrics by The Beatles and GPT:", lines=20)
-examples = [['In my dream I am', 0.7], ['I don\'t feel alive', 0.7]]
+input_box = gr.Textbox(label="Input prompt:", placeholder="Write the start of a song here", value="In my dreams I am", lines=2, max_lines=5)
+output_box = gr.Textbox(label="Lyrics by The Beatles and GPT:", lines=25)
+
+# Specify examples
+examples = [['In my dreams I am', 0.7], ['I don\'t feel alive when', 0.7]]
+
+# Layout and text above the App
 title='Beatles lyrics generator based on GPT2'
-description='A medium class GPT2 model was fine-tuned on lyrics from The Beatles to generate Beatles-like text. Give it a try!'
-temperature = gr.Slider(minimum=0.0, maximum=1.0, step=0.1, label="Temperature (high = sensitive for low probability tokens)", value=0.7, show_label=True)
+description="<p style='text-align: center'>A medium class GPT2 model was fine-tuned on lyrics from The Beatles to generate Beatles-like text. Give it a try!</p>"
+article="""<p style='text-align: left'>A couple of data scientists working for <a href='https://cmotions.nl/' targeet="_blank">Cmotions</a> came together to construct a Language Generation model that will ouput Beatles-like text. 
+        We used several models that were able to load in Colab and choose <a href='https://huggingface.co/gpt2-medium' target='_blank'>GPT2-medium</a> as the winner. Further we've put together a <a href='https://huggingface.co/datasets/cmotions/Beatles_lyrics' target='_blank'> Huggingface dataset</a> containing all known lyrics created by 
+        The Beatles. <a href='https://www.theanalyticslab.nl/blogs/' target='_blank'>Read this blog </a> to see how this model was build in a Python the notebook using Huggingface.
+        The default output contains 100 tokens and has a repetition penalty of 1.0. 
+         </p>"""
+
+# Let users select their own temperature and top-p
+temperature = gr.Slider(minimum=0.1, maximum=1.0, step=0.1, label="Temperature (high = sensitive for low probability tokens)", value=0.7, show_label=True)
+top_p = gr.Slider(minimum=0.1, maximum=1.0, step=0.1, label="Top-p (sample next possible words from given probability p)", value=0.5, show_label=True)
+
+# Can I put examples in an input dropdown box?
+#examples_dropdown = gr.Dropdown(choises=examples, value = 'In my dreams I am', label='Examples', show_label=True)
 
 # Use generate Beatles function in demo-app Gradio
 gr.Interface(fn=generate_beatles
-             , inputs=[input_box, temperature]
+             , inputs=[input_box, temperature, top_p]
              , outputs=output_box
-             , examples=examples
+             #, examples=examples # output is not very fancy as you have to specify all inputs for every example
              , title=title
              , description=description
+             , article=article
+             , allow_flagging='never'
              ).launch()