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import gradio as gr
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from transformers import pipeline
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model_name = "AventIQ-AI/gpt2-next-word-prediction"
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predictor = pipeline("text-generation", model=model_name)
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def predict_next_word(prompt):
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result = predictor(prompt, max_length=len(prompt.split()) + 1, num_return_sequences=1)
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return result[0]['generated_text']
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examples = [
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["Artificial intelligence is"],
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["The future of technology"],
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["Machine learning enables"],
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["Deep learning models are"],
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]
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def main():
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with gr.Blocks(theme="soft") as demo:
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gr.Markdown("""
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# 🚀 Next-Word Prediction
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Enter a partial sentence, and the model will predict the next word.
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""")
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with gr.Row():
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input_text = gr.Textbox(label="Enter a sentence", placeholder="Type here...")
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predict_btn = gr.Button("🔮 Predict Next Word")
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output_text = gr.Textbox(label="Predicted Sentence", interactive=False)
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predict_btn.click(predict_next_word, inputs=input_text, outputs=output_text)
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gr.Examples(examples, inputs=input_text)
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demo.launch()
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if __name__ == "__main__":
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main() |
