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The PAI Python SDK is provided by Alibaba Cloud's Platform for Artificial Intelligence (PAI). It offers a user-friendly High-Level API, enabling machine learning engineers to easily train and deploy models on PAI using Python, streamlining the machine learning workflow.
Install the PAI Python SDK using the following command, which supports Python versions >= 3.6 (it is recommended to use Python >= 3.8):
python -m pip install alipaiFind detailed documentation, including API references and user guides, in the docs directory or visit PAI Python SDK Documentation.
- Submit a custom training job
The following example demonstrates how to submit a custom training job to PAI:
from pai.estimator import Estimator
from pai.image import retrieve
est = Estimator(
# Retrieve the latest PyTorch image provided by PAI
image_uri=retrieve(
framework_name="PyTorch", framework_version="latest"
).image_uri,
command="echo hello",
# Optionally, specify the source_dir to upload your training code:
# source_dir="./train_src",
instance_type="ecs.c6.large",
)
# Submit the training job
est.fit()
print(est.model_data())- Deploy Large Language Model
PAI provides numerous pretrained models that you can easily deploy using the PAI Python SDK:
from pai.model import RegisteredModel
# Retrieve the QWen-7b model provided by PAI
qwen_model = RegisteredModel("qwen-7b-chat-lora", model_provider="pai")
# Deploy the model
p = qwen_model.deploy(service_name="qwen_service")
# Call the service
p.predict(
data={
"prompt": "How to install PyTorch?",
"system_prompt": "Act like you are programmer with 5+ years of experience.",
"temperature": 0.8,
}
)For more details, please refer to the PAI Python SDK Documentation.
Contributions to the PAI Python SDK are welcome. Please read our contribution guidelines in the CONTRIBUTING file.
PAI Python SDK is developed by Alibaba Cloud and licensed under the Apache License (Version 2.0).
For support or inquiries, please open an issue on the GitHub repository or contact us in the DingTalk group:
