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| from transformers import pipeline | |
| import gradio as gr | |
| PIPELINES = {} | |
| def build_pipeline(size): | |
| global PIPELINES | |
| if size in PIPELINES: | |
| return PIPELINES[size] | |
| PIPELINES[size] = pipeline( | |
| "text2text-generation", model=f"google/flan-t5-{size}", max_length=256 | |
| ) | |
| return PIPELINES[size] | |
| def greet(input_text, size): | |
| pipe = build_pipeline(size) | |
| return pipe(input_text)[0]["generated_text"] | |
| demo = gr.Interface( | |
| fn=greet, | |
| inputs=[ | |
| gr.Textbox(lines=2, placeholder="Enter your task text..."), | |
| gr.Radio(choices=["small", "base", "large", "xl"], value="base"), | |
| ], | |
| outputs=[gr.Textbox(lines=2)], | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() | |