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GPT2 - 文本生成转换器:如何使用和启动服务

什么是文本生成?输入一些文本,模型将预测后续文本会是什么。

听起来不错。不过不亲自尝试模型怎么可能有趣?

如何使用

模型将自动下载

from transformers import pipeline, set_seed

generator = pipeline("text-generation", model="gpt2")
set_seed(42)


def predict(text: str) -> list:
    return generator(text, max_length=50, num_return_sequences=3)

就是这样!

让我们尝试一下:

predict("You look amazing today,")

结果:

[{'generated_text': 'You look amazing today, guys. If you\'re still in school and you still have a job where you work in the field… you\'re going to look ridiculous by now, you\'re going to look really ridiculous."\n\nHe turned to his friends'},
 {'generated_text': 'You look amazing today, aren\'t you?"\n\nHe turned and looked at me. He had an expression that was full of worry as he looked at me. Even before he told me I\'d have sex, he gave up after I told him'},
 {'generated_text': 'You look amazing today, and look amazing in the sunset."\n\nGarry, then 33, won the London Marathon at age 15, and the World Triathlon in 2007, the two youngest Olympians to ride 100-meters. He also'}]

让我们看看第一个结果。

You look amazing today, guys. If you're still in school and you still have a job where you work in the field… you're going to look ridiculous by now, you're going to look really ridiculous."  He turned to his friends

🤣 这就是我们要找的东西!如果再次运行预测,每次都会给出不同的结果。

如何部署

安装Pinferencia

$ pip install "pinferencia[streamlit]"
---> 100%

创建服务

app.py
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from transformers import pipeline, set_seed

from pinferencia import Server, task

generator = pipeline("text-generation", model="gpt2")
set_seed(42)


def predict(text: str) -> list:
    return generator(text, max_length=50, num_return_sequences=3)


service = Server()
service.register(
    model_name="gpt2",
    model=predict,
    metadata={"task": task.TEXT_TO_TEXT},
)

启动服务

$ uvicorn app:service --reload
INFO:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
INFO:     Started reloader process [xxxxx] using statreload
INFO:     Started server process [xxxxx]
INFO:     Waiting for application startup.
INFO:     Application startup complete.
$ pinfer app:service --reload

Pinferencia: Frontend component streamlit is starting...
Pinferencia: Backend component uvicorn is starting...

测试服务

打开http://127.0.0.1:8501,模板Text to Text会自动选中。

UI

curl -X 'POST' \
    'http://127.0.0.1:8000/v1/models/gpt2/predict' \
    -H 'accept: application/json' \
    -H 'Content-Type: application/json' \
    -d '{
        "id": "string",
        "parameters": {},
        "data": "You look amazing today,"
    }'

结果:

{
    "id": "string",
    "model_name": "gpt2",
    "data": [
        {
            "generated_text": "You look amazing today, I was in front of my friends. I wanted everyone to see me. But that's all. No one really cares about me in the eyes of the whole world unless I love them.\"\n\nIn a second Facebook post"
        },
        {
            "generated_text": "You look amazing today, and I know I am going to get the job done! So thank you all for all those donations, money, help, and hugs. I hope to see you again soon."
        },
        {
            "generated_text": "You look amazing today, but I will have to wait until early June for what will go down as the first NBA championship (a thing I had been expecting). If it's not the biggest, it is also not great. Now let's look at"
        }
    ]
}
test.py
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import requests

response = requests.post(
    url="http://localhost:8000/v1/models/gpt2/predict",
    json={
        "data": "You look amazing today,"
    },
)
print("Prediction:", response.json()["data"])

运行python test.py并打印结果:

Prediction: [
    {
        "generated_text": "You look amazing today, I was in front of my friends. I wanted everyone to see me. But that's all. No one really cares about me in the eyes of the whole world unless I love them.\"\n\nIn a second Facebook post"
    },
    {
        "generated_text": "You look amazing today, and I know I am going to get the job done! So thank you all for all those donations, money, help, and hugs. I hope to see you again soon."
    },
    {
        "generated_text": "You look amazing today, but I will have to wait until early June for what will go down as the first NBA championship (a thing I had been expecting). If it's not the biggest, it is also not great. Now let's look at"
    }
]

更酷的是,访问 http://127.0.0.1:8000,您将拥有一个完整的 API 文档。

您甚至也可以在那里发送预测请求!