app.py

import gradio as gr
from transformers import GPT2LMHeadModel, GPT2Tokenizer

# Load the GPT-2 model and tokenizer
model_name = "gpt2"
model = GPT2LMHeadModel.from_pretrained(model_name)
tokenizer = GPT2Tokenizer.from_pretrained(model_name)

# Define the sentence completion function
def complete_sentence(sentence):
	input_ids = tokenizer.encode(sentence, return_tensors="pt")
	output = model.generate(input_ids, max_length=50, num_return_sequences=1)
	completed_sentence = tokenizer.decode(output[0], skip_special_tokens=True)
	return completed_sentence

# Create the Gradio interface
iface = gr.Interface(
	fn=complete_sentence,
	inputs="text",
	outputs="text",
	title="Sentence Completion",
	description="Enter a sentence to complete",
	example="I love to"
)

# Launch the Gradio interface
if __name__ == "__main__":
	iface.launch()