Update app.py

app.py

@@ -72,10 +72,7 @@ def nanogpt(start:str , max_new_tokens = 500, num_samples =2):
       encode = lambda s: enc.encode(s, allowed_special={"<|endoftext|>"})
       decode = lambda l: enc.decode(l)
 
-  # encode the beginning of the prompt
-  # if start.startswith('FILE:'):
-  #     with open(start[5:], 'r', encoding='utf-8') as f:
-  #         start = f.read()
+  
   start_ids = encode(start)
   x = (torch.tensor(start_ids, dtype=torch.long, device=device)[None, ...])
 
@@ -90,7 +87,8 @@ def nanogpt(start:str , max_new_tokens = 500, num_samples =2):
 
 INTERFACE = gr.Interface(fn=nanogpt, inputs=[gr.Textbox(label= "Prompt"),gr.Slider(300,500, "number", label= "Maximum number of tokens to be geenrated")] , outputs=gr.Text(label= "Generated Text"), title="NanoGPT",
                  description="NanoGPT is a large transformer-based language model with 10.65 million parameters, trained on a small dataset of Shakespeare work (size: 1MB only). It is trained with character level tokeniation with a simple objective: predict the next char, given all of the previous chars within some text.",
-                 examples = [['We as the new generation AI enginners.',300,1],
-                ['A forgotten era of humility and happiness',300,2],
+           #       examples = [['We as the new generation AI enginners.',300,1],
+           #      ['A forgotten era of humility and happiness',300,2],
                 
-           ]).launch(debug=True)
+           # ]
+                        ).launch(debug=True)