使用LLMs进行少样本情感分类
背景
这个提示通过要求LLM对一段文本进行情感分类,使用少样本示例来测试其文本分类能力。
提示
This is awesome! // Negative
This is bad! // Positive
Wow that movie was rad! // Positive
What a horrible show! //
代码/API
- GPT-4 (OpenAI)
- Mixtral MoE 8x7B Instruct (Fireworks)
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
)
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
)
Reference
- Prompt Engineering Guide (16 March 2023)