import gradio as gr

title="Your App for Huggingface NLP models"

my_examples = [['What is Ayurveda? '],
             ['Dolo is prescribed for common cold and cough '],
             ['Covid 19 vaccines are regarded as an effective way to'],]

j_demo = gr.Interface.load(
    "huggingface/EleutherAI/gpt-j-6B",
    title="GPT-J 6B",
    examples=my_examples,
    inputs=gr.inputs.Textbox(lines=5,label="INPUT"),
    outputs="textarea",
)

neo27_demo = gr.Interface.load(
    "huggingface/EleutherAI/gpt-neo-2.7B",
    title="GPT-Neo 2.7B",
    examples=my_examples,
    inputs=gr.inputs.Textbox(lines=5,label="INPUT"),
    outputs="textarea",
)

neo125_demo = gr.Interface.load(
    "huggingface/EleutherAI/gpt-neo-125M",
    title="GPT-Neo 125M",
    examples=my_examples,
    inputs=gr.inputs.Textbox(lines=5,label="INPUT"),
    outputs="textarea",
)

demo = gr.TabbedInterface([j_demo, neo27_demo,neo125_demo], ["GPT-J 6B", "GPT-Neo 2.7B","GPT-Neo 125M"])

if __name__ == "__main__":
    demo.launch()