Update app.py

app.py

@@ -1,18 +1,25 @@
 import gradio as gr
 from gradio import mix
 
-title = "trustworthy artificial intelligence workshop - content generator"
+#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")
+#io1 = gr.Interface.load("huggingface/distilgpt2")
+
+from transformers import pipeline, set_seed
+generator = pipeline('text-generation', model='gpt2')
+set_seed(42)
+
 
 io2 = gr.Interface.load("huggingface/gpt2-large")
+#TODO: 1) seed 2) output lenght
 
-io3 = gr.Interface.load("huggingface/gpt2-medium")
+#io3 = gr.Interface.load("huggingface/gpt2-medium")
 
-io4 = gr.Interface.load("huggingface/gpt2-xl")
+#io4 = gr.Interface.load("huggingface/gpt2-xl")
 
 def inference(text, model):
+    """
     if model == "gpt2-large":
         outtext = io2(text)
     elif model == "gpt2-medium":
@@ -21,15 +28,21 @@ def inference(text, model):
         outtext = io4(text)
     else:
         outtext = io1(text)
+    """
+    #outtext = io2(text)
+    outtext = generator(text, max_length=30, num_return_sequences=5)
     return outtext   
     
      
 
 gr.Interface(
     inference, 
-    [gr.inputs.Textbox(label="Input"),gr.inputs.Dropdown(choices=["distilgpt2","gpt2-medium","gpt2-large","gpt2-xl"], type="value", default="gpt2-medium", label="model")
+    [gr.inputs.Textbox(label="Input", placeholder="trustworthy artificial intelligence")]
+    #,gr.inputs.Dropdown(choices=["distilgpt2","gpt2-medium","gpt2-large","gpt2-xl"], type="value", default="gpt2-medium", label="model")
 ], 
-    gr.outputs.Textbox(label="Output"),
-    title=title,
-    description=description,
-    cache_examples=True).launch(enable_queue=True)
+    gr.outputs.Textbox(label="gpt-2 proposal"),
+    #title=title,
+    #description=description,
+    cache_examples=True).launch(enable_queue=True)
+
+#TODO: add credits at bottom