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import gradio as gr
from transformers import GPT2LMHeadModel, GPT2Tokenizer
# Load pre-trained model
tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
model = GPT2LMHeadModel.from_pretrained("gpt2")
def generate_text(prompt):
inputs = tokenizer.encode(prompt, return_tensors="pt")
outputs = model.generate(inputs, max_length=150, num_return_sequences=1, temperature=0.7)
generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
return generated_text
iface = gr.Interface(fn=generate_text, inputs="text", outputs="text")
iface.launch()
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