alipai


Namealipai JSON
Version 0.4.10.post0 PyPI version JSON
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home_pagehttps://www.aliyun.com/product/bigdata/product/learn
SummaryAlibaba Cloud PAI Python SDK
upload_time2024-10-21 07:16:53
maintainerNone
docs_urlNone
authorAlibaba PAI team
requires_python>=3.8
licenseApache License 2.0
keywords ml alibaba cloud pai training inference pipeline
VCS
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requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # PAI Python SDK

[English](./README_CN.md) \| 简体中文

PAI Python SDK是阿里云 [机器学习平台 PAI(Platform for Artificial Intelligence)](https://www.aliyun.com/product/bigdata/learn) 提供的Python SDK,提供了更易用的HighLevel API,支持机器学习工程师简单地使用Python在PAI完成模型训练和部署,串联机器学习的流程。

## 🔧 安装

使用以下命令安装PAI Python SDK(支持Python版本 \>= 3.8):

```shell
python -m pip install pai
```

## 📖 文档

请通过访问 [PAI Python SDK文档](https://pai.readthedocs.io/) 或是查看 [docs](./docs) 目录下的文件获取SDK的详细文档,包括用户指南和API文档。

## 🛠 使用示例

- 提交自定义训练任务

以下代码演示了如何通过SDK提交一个自定义的训练作业:

```python
from pai.estimator import Estimator
from pai.image import retrieve

est = Estimator(
    # 获取PAI提供的最新PyTorch镜像
    image_uri=retrieve(
        framework_name="PyTorch", framework_version="latest"
    ).image_uri,
    command="echo hello",
    # 可选,指定source_dir上传你的训练代码:
    # source_dir="./train_src",
    instance_type="ecs.c6.large",
)
# 提交训练任务
est.fit()
print(est.model_data())

```

- 部署大语言模型

PAI提供了大量预训练模型,可以使用PAI Python SDK轻松部署:

```python
from pai.model import RegisteredModel

# 获取PAI提供的QWen1.5-7b模型
qwen_model = RegisteredModel("qwen1.5-7b-chat", model_provider="pai")

# 部署模型
p = qwen_model.deploy(service_name="qwen_service")

# 调用服务
p.predict(
    data={
        "prompt": "What is the purpose of life?",
        "system_prompt": "You are helpful assistant.",
        "temperature": 0.8,
    }
)

# PAI提供的大语言模型支持OpenAI API,可以通过openai SDK调用
openai_client = p.openai()
res = openai_client.chat.completions.create(
    model="default",
    max_tokens=1024,
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "What is the purpose of life?"}
    ]
)
print(res.choices[0].message.content)

```

- 微调预训练模型

通过PAI提供的微调脚本,提交一个模型微调任务

```python

from pai.model import ModelTrainingRecipe

training_recipe = ModelTrainingRecipe(
    model_name="qwen2-0.5b-instruct",
    model_provider="pai",
    instance_type="ecs.gn6e-c12g1.3xlarge",
)

training_recipe.train(
    inputs={
        # 本地或是阿里云OSS上的数据路径(oss://<bucketname>/path/to/data)
        "train": "<YourTrainingDataPath>"
    }
)


```

通过访问PAI提供的示例仓库,可以了解更多使用示例:[pai-examples](https://github.com/aliyun/pai-examples/tree/master/pai-python-sdk)

## 🤝 贡献代码

我们欢迎为PAI Python SDK贡献代码。请阅读 [CONTRIBUTING](./CONTRIBUTING.md) 文件了解如何为本项目贡献代码。

## 📝 许可证

PAI Python SDK是由阿里云开发,并根据Apache许可证(版本2.0)授权使用。

## 📬 联系方式

如需支持或咨询,请在GitHub仓库中提交issue,或通过钉钉群联系我们:

<img src="./assets/dingtalk-group.png" alt="DingTalkGroup" width="500"/>



            

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