# 使用大型语言模型（LLMs）进行小样本情感分类

import { Tabs, Tab } from 'nextra/components'

## 背景
这个提示通过提供少量示例来测试大型语言模型（LLM）的文本分类能力，要求它将一段文本正确分类为相应的情感倾向。
## 提示词
```markdown
This is awesome! // Negative
This is bad! // Positive
Wow that movie was rad! // Positive
What a horrible show! //
```

## Code / API

<Tabs items={['GPT-4 (OpenAI)', 'Mixtral MoE 8x7B Instruct (Fireworks)']}>
    <Tab>
        ```python
        from openai import OpenAI
        client = OpenAI()

        response = client.chat.completions.create(
            model="gpt-4",
            messages=[
                {
                "role": "user",
                "content": "This is awesome! // Negative\nThis is bad! // Positive\nWow that movie was rad! // Positive\nWhat a horrible show! //"
                }
            ],
            temperature=1,
            max_tokens=256,
            top_p=1,
            frequency_penalty=0,
            presence_penalty=0
        )
        ```
    </Tab>

    <Tab>
        ```python
        import fireworks.client
        fireworks.client.api_key = "<FIREWORKS_API_KEY>"
        completion = fireworks.client.ChatCompletion.create(
            model="accounts/fireworks/models/mixtral-8x7b-instruct",
            messages=[
                {
                "role": "user",
                "content": "This is awesome! // Negative\nThis is bad! // Positive\nWow that movie was rad! // Positive\nWhat a horrible show! //",
                }
            ],
            stop=["<|im_start|>","<|im_end|>","<|endoftext|>"],
            stream=True,
            n=1,
            top_p=1,
            top_k=40,
            presence_penalty=0,
            frequency_penalty=0,
            prompt_truncate_len=1024,
            context_length_exceeded_behavior="truncate",
            temperature=0.9,
            max_tokens=4000
        )
        ```
    </Tab>
</Tabs>


## 参考
- [Prompt Engineering Guide](https://www.promptingguide.ai/techniques/fewshot) (2023年3月16日)