Vertex AI使用指南.md

• https://cloud.google.com/vertex-ai?hl=zh-cn
• Vertex AI 使用入门

文本数据

提示词设计

Overview of text prompt design，示例：

Text:
Question:
Answer:
Categories:
Options:

示例2（关联一致性）：

Classify the sentiment of the following text as positive or negative.
Text: I love chocolate.
Sentiment:

分类

• 解读文本分类模型的预测结果

总结

• Design summarization prompts

总结文本

Provide a summary for the following article:
...
Write an abstract of this article:
...
Write a creative title for the text.
...

总结对话

Summarize the following conversation.
A: ...
B: ...

提取

• Design extraction prompts

使用场景

The following are common use cases for extraction:

• Named entity recognition (NER): Extract named entities from text, including people, places, organizations, and dates.
• Relation extraction: Extract the relationships between entities in text, such as family relationships between people.
• Event extraction: Extract events from text, such as project milestones and product launches.
• Question answering: Extract information from text to answer a question.

模型

text-bison

示例

Prompt:

Extract the technical specifications from the text below in a JSON format. Valid fields are name, network, ram, processor, storage, and color.
Text: Google Pixel 7, 5G network, 8GB RAM, Tensor G2 processor, 128GB of storage, Lemongrass
JSON:

Response:

{
  "name": "Google Pixel 7",
  "network": "5G",
  "ram": "8GB",
  "processor": "Tensor G2",
  "storage": "128GB",
  "color": "Lemongrass"
}

Vertex AI API

• Quickstart using the Vertex AI API 文中给了提示词示例和参数示例，重点参考
• 从文本实体提取模型获取预测结果 支持批量预测
• Google Vertex AI Client for Java

价格

• Vertex AI 价格