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app.py

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+from transformers import GPT2Tokenizer, GPT2LMHeadModel
+import torch
+
+# Initialize the tokenizer and model
+tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
+model = GPT2LMHeadModel.from_pretrained("gpt2")
+
+# Set the model to evaluation mode
+model.eval()
+
+# Prompt text
+prompt = "face generating code"
+
+# Encode the prompt text
+input_ids = tokenizer.encode(prompt, return_tensors="pt")
+
+# Generate text
+with torch.no_grad():
+    output = model.generate(input_ids=input_ids, max_length=500)
+
+# Decode the generated text
+generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
+
+print(generated_text)