Datasets:
metadata
license: mit
task_categories:
- text-classification
language:
- vi
- en
tags:
- textclassification
- modelrouting
- routing
- gptrouting
- fewshot
size_categories:
- n<1K
pretty_name: gpt_routing
Model Description
This model is designed for prompt routing to determine whether a prompt should be handled by GPT-4o or GPT-3.5. The goal is to reduce costs, as GPT-4o is significantly more expensive (10x the cost of GPT-3.5).
The dataset is intended for few-shot learning, which is why it contains a small number of prompts in two languages: Vietnamese and English.
Labels were manually assigned based on specific use cases. You can expand the classification to include other models such as LLaMA or GPT-4, depending on your requirements.
- gpt-4o: Handles complex questions that require deep thinking and analysis, such as math problems, multiple-choice homework, and tests.
- gpt-3.5: Handles simpler questions primarily for information retrieval, where answers are readily available in the documents from a Retrieval-Augmented Generation (RAG) system, as well as straightforward code and explanations.