update for huggingface spaces

app.py

@@ -140,29 +140,25 @@ Label:''', 1, 2, 0.2, 1.0, 1.0, "\\n,</s>"]
 ]
 
 
-def main():
-    iface = gr.Interface(
-        fn=infer,
-        allow_flagging="never",
-        inputs=[
-            gr.Textbox(lines=20),  # prompt
-            gr.Slider(0, 256, value=1), #min_length
-            gr.Slider(1, 384, value=20),  # max_tokens
-            gr.Slider(0.0, 1.0, value=0.2),  # temperature
-            gr.Slider(0.0, 1.0, value=0.9),  # top_p
-            gr.Slider(0.9, 3.0, value=1.0),  # repetition penalty
-            gr.Textbox(lines=1, value="\\n,</s>") # stop
-        ],
-        outputs=[gr.Textbox(lines=7, label="BLOOM OUTPUT:"), gr.Textbox(lines=7,label="BLOOMZ OUTPUT:")],
-        
-        examples=examples,
-        cache_examples=True,
-        title="BLOOM vs BLOOMZ",
-        description='''<p>Compare outputs of the BLOOM and BLOOMZ 176 billion parameter models using the [Petals](https://petals.ml/) network. Please consider joining the Petals network to help speed up inference.</p><p>Big thanks to [RFTCapital](https://www.rftcapital.com) for providing initial compute resources.</p>'''
-    )
-
-    iface.launch(debug=True, share=False)
-
-
-if __name__ == '__main__':
-    main()
+
+iface = gr.Interface(
+    fn=infer,
+    allow_flagging="never",
+    inputs=[
+        gr.Textbox(lines=20),  # prompt
+        gr.Slider(0, 256, value=1), #min_length
+        gr.Slider(1, 384, value=20),  # max_tokens
+        gr.Slider(0.0, 1.0, value=0.2),  # temperature
+        gr.Slider(0.0, 1.0, value=0.9),  # top_p
+        gr.Slider(0.9, 3.0, value=1.0),  # repetition penalty
+        gr.Textbox(lines=1, value="\\n,</s>") # stop
+    ],
+    outputs=[gr.Textbox(lines=7, label="BLOOM OUTPUT:"), gr.Textbox(lines=7,label="BLOOMZ OUTPUT:")],
+    
+    examples=examples,
+    cache_examples=True,
+    title="BLOOM vs BLOOMZ",
+    description='''<p>Compare outputs of the BLOOM and BLOOMZ 176 billion parameter models using the [Petals](https://petals.ml/) network. Please consider joining the Petals network to help speed up inference.</p><p>Big thanks to [RFTCapital](https://www.rftcapital.com) for providing initial compute resources.</p>'''
+)
+
+iface.launch(debug=True, share=False)