Update app.py

app.py

@@ -3,46 +3,18 @@ import gradio as gr
 from gradio import mix
 from transformers import pipeline, set_seed
 
-#title = "trustworthy artificial intelligence workshop - content generator"
-description = "based on the gpt2 demo interface by <a href='https://huggingface.co/spaces/docs-demos/gpt2/tree/main'>ahsen khaliq</a>"
-
-#io1 = gr.Interface.load("huggingface/distilgpt2")
-
 generator = pipeline('text-generation', model='gpt2')
 
-
-#io2 = gr.Interface.load("huggingface/gpt2-large")
-
-#io3 = gr.Interface.load("huggingface/gpt2-medium")
-
-#io4 = gr.Interface.load("huggingface/gpt2-xl")
-
 def inference(text, seed):
-    """
-    if model == "gpt2-large":
-        outtext = io2(text)
-    elif model == "gpt2-medium":
-        outtext = io3(text)
-    elif model == "gpt2-xl":
-        outtext = io4(text)
-    else:
-        outtext = io1(text)
-    """
-    #outtext = io2(text)
     set_seed(int(seed))
     outtext = generator(text, max_length=100, num_return_sequences=1)['generated_text'] #get the string from the return dict with key 'generated text'
     return outtext   
     
-     
-
 gr.Interface(
     inference, 
-    [gr.inputs.Radio(choices=["trustworthy artificial intelligence"], label="input"), gr.inputs.Slider(minimum=0., maximum=1000.,label="seed")],
-    #,gr.inputs.Dropdown(choices=["distilgpt2","gpt2-medium","gpt2-large","gpt2-xl"], type="value", default="gpt2-medium", label="model")], 
+    [gr.inputs.Radio(choices=["trustworthy artificial intelligence"], label="input"), gr.inputs.Slider(minimum=0., maximum=1000.,label="seed")], 
     gr.outputs.Textbox(label="gpt-2 proposal"),
-    #title=title,
-    #description=description,
-    cache_examples=True).launch(enable_queue=True,
-    allow_flagging="manual")
+    cache_examples=True,
+    allow_flagging="manual").launch(enable_queue=True)
 
 #TODO: add credits at bottom