Create app.py

app.py

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+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()