update

app.py

@@ -60,7 +60,7 @@ demo = gr.Blocks()
 with demo:
   gr.Markdown("<h1><center>Step By Step With Bloom</center></h1>")
   gr.Markdown(
-        """ [BigScienceW Bloom](https://twitter.com/BigscienceW) \n\n Large language models have demonstrated a capability of 'Chain-of-thought reasoning'. Some amazing researchers( [Jason Wei et al.](https://arxiv.org/abs/2206.07682)) recently found out that by addding **Lets think step by step** it improves the model's zero-shot performance. Some might say — You can get good results out of LLMs if you know how to speak to them."""
+        """ [BigScienceW Bloom](https://twitter.com/BigscienceW) \n\n Large language models have demonstrated a capability of 'Chain-of-thought reasoning'. Some amazing researchers( [Jason Wei et al.](https://arxiv.org/abs/2206.07682)) recently found out that by addding **Lets think step by step** it improves the model's zero-shot performance. Some might say — You can get good results out of LLMs if you know how to speak to them.\n\nThis Space is created by [Yuvraj Sharma](https://twitter.com/yvrjsharma)"""
         )
   with gr.Row():
     example_prompt = gr.Radio( ["Q: A juggler can juggle 16 balls. Half of the balls are golf balls, and half of the golf balls are blue. How many blue golf balls are there?\nA: Let’s think step by step.\n", "Q: Roger has 5 tennis balls already. He buys 2 more cans of tennis balls. Each can has 3 tennis balls. How many tennis balls does he have now?\nA: Let’s think step by step.\n", "Q: On an average Joe throws 25 punches per minute. His fight lasts 5 rounds of 3 minutes each. How many punches did he throw?\nA:  Let’s think about this logically.\n"], label= "Choose a sample Prompt")