| import gradio as gr | |
| from transformers import pipeline | |
| # Load your model | |
| summarizer = pipeline("summarization", model="manohar02/Llama-2-7b-finetune") | |
| # Define the summarization function | |
| def summarize(text): | |
| summary = summarizer(text, max_length=2048, min_length=10, do_sample=False) | |
| return summary[0]['summary_text'] | |
| # Set up the Gradio interface | |
| iface = gr.Interface(fn=summarize, inputs="text", outputs="text", title="Text Summarizer") | |
| if __name__ == "__main__": | |
| iface.launch() | |