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:((((

app.py

@@ -1,22 +0,0 @@
-
-
-import gradio as gr
-
-# Initialize tokenizer and model
-	
-import transformers
-tokenizer = transformers.GPT2Tokenizer.from_pretrained('gpt2')
-model = GPT2LMHeadModel.from_pretrained('gpt2')
-
-# Create a function to generate text
-def generate_text(input_text):
-    # Encode the input text
-    input_ids = tokenizer.encode(input_text, return_tensors='pt')
-    # Generate the output text
-    output_ids = model.generate(input_ids, max_length=50, do_sample=True, top_k=50, top_p=0.95, num_return_sequences=1)
-    # Decode the output text
-    output_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
-    return output_text
-
-# Create the interface
-gr.Interface(fn=generate_text, inputs="text", outputs="text", title="Chat GPT").launch()