Gradio使用实例

Gradio 是一个用于构建交互式界面的 Python 库，可以轻松创建和共享机器学习模型的 Web 应用程序。下面是一个简单的 Gradio 使用示例:

import gradio as gr


def evaluate(*args):
    args_str = ' '.join(str(arg) for arg in args)
    return args_str

gr.Interface(
        fn=evaluate,
        inputs=[
            gr.components.Textbox(
                lines=2,
                label="Instruction",
                placeholder="Tell me about alpacas.",
            ),
            gr.components.Textbox(lines=2, label="Input", placeholder="none"),
            gr.components.Slider(minimum=0, maximum=1, value=0.1, label="Temperature"),
            gr.components.Slider(minimum=0, maximum=1, value=0.75, label="Top p"),
            gr.components.Slider(minimum=0, maximum=100, step=1, value=40, label="Top k"),
            gr.components.Slider(minimum=1, maximum=4, step=1, value=4, label="Beams"),
            gr.components.Slider(minimum=1, maximum=2000, step=1, value=128, label="Max tokens"),
            gr.components.Checkbox(label="Stream output"),
        ],
        outputs=[
            gr.inputs.Textbox(
                lines=5,
                label="Output",
            )
        ],
        title="🦙🌲 Alpaca-LoRA",
        description="Alpaca-LoRA is a 7B-parameter LLaMA model finetuned to follow instructions. It is trained on the [Stanford Alpaca](https://github.com/tatsu-lab/stanford_alpaca) dataset and makes use of the Huggingface LLaMA implementation. For more information, please visit [the project's website](https://github.com/tloen/alpaca-lora).",  # noqa: E501
    ).queue().launch(server_name="0.0.0.0", share=False)