| import gradio as gr | |
| from transformers import pipeline, set_seed | |
| generator = pipeline('text-generation', model='flax-community/miniLM-L6-h384-uncased', device=0) | |
| def generate_text(prompt, length=50, temperature=0.7, seed=42): | |
| set_seed(seed) | |
| output = generator(prompt, max_length=length, do_sample=True, temperature=temperature) | |
| return output[0]['generated_text'] | |
| inputs = gr.inputs.Textbox(lines=5, label="Prompt") | |
| outputs = gr.outputs.Textbox(label="Output Text") | |
| temperature_slider = gr.inputs.Slider(minimum=0.1, maximum=1.5, default=0.7, label="Temperature") | |
| length_slider = gr.inputs.Slider(minimum=10, maximum=200, default=50, label="Length") | |
| seed_input = gr.inputs.Number(default=42, label="Seed") | |
| gr.Interface(fn=generate_text, inputs=[inputs, length_slider, temperature_slider, seed_input], outputs=outputs, title="Generative AI", description="Use MiniLM to generate text based on a prompt.").launch() | |