task_categories:conversational task_categories:question-answering task_categories:text-generation size_categories:1K<n<10K language:en license:apache-2.0 Physics Biology Math Chemistry Culture Logic Roleplay region:us
---
license: apache-2.0
task_categories:
- conversational
- question-answering
- text-generation
language:
- en
tags:
- Physics
- Biology
- Math
- Chemistry
- Culture
- Logic
- Roleplay
pretty_name: Puffin
size_categories:
- 1K<n<10K
---

## This is the Official Puffin dataset. Exactly 3,000 examples with each response created using GPT-4.

 - Comprised of over 2,000 multi-turn conversations between GPT-4 and real humans.

 - Average context length per conversation is over 1,000 tokens. (will measure this more accurately soon)

 - Average turns per conversation is more than 10. (will measure this more accurately soon)

 - The other portion of Puffin is made of manually curated subsets of the following (All responses synthesized using GPT-4):

CamelAI/Physics
CamelAI/Math
CamelAI/Biology
CamelAI/Chemistry

A majority of the real multi-turn conversations are made up of a curated subset of the original ShareGPT dataset.

 - Extensive cleaning was done to filter out instances of overt AI moralizing or related behaviour, such as "As an AI language model" and "September 2021"

 - Most importantly, we narrowed down the ShareGPT dataset to strictly only GPT-4 examples. Knowing which ShareGPT examples were GPT-4 vs GPT-3.5 was a task that would've been much more arduous if it wasn't for the help of folks over at OpenChat, whom annoteated the neccessary examples.


During the curation process, there can be some relatively arduos steps when it comes to actually executing on the best experimentation or concepts for how to filter examples out. Luckily there is folks over at NousResearch that helped expedite this process with little to no sacrifices in quality, big thank you to J-Supha specifically for making these types of significant contributions.

Along with J-Supha, some other people are worth mentioning, these are the folks that helped on long late night calls to help debug and/or get Puffin training on Llama-2 Asap, all within 12 hours of Llama-2 being announced.

 - Emozilla, Teknium, Caseus. And of course thank you to RedmondAI for sponsoring the training compute!

## Future Plans & How you can help!

This is a relatively early build amongst the grand plans for the future of what I plan to work on! 

In the near future we plan on leveraging the help of domain specific expert volunteers to eliminate any mathematically/verifiably incorrect answers from our training curations. 

If you have at-least a bachelors in mathematics, physics, biology or chemistry and would like to volunteer even just 30 minutes of your expertise time, please contact LDJ on discord! 

