OpenAI has caught the world by storm with ChatGPT.
ChatGPT is a powerful open-source natural language processing (NLP) machine learning model that can be fine-tuned to improve its accuracy and, more importantly, give you the style of answer you’re after.
One of the critical points for success when fine-tuning ChatGPT is the choice of specially made prompts.
While fine-tuning works well for healthy prompts, fine-tuning can create some problematic scenarios.
By feeding chatGPT-specific prompt formulas, ChatGPT can be fine-tuned to break the rules and provide answers outside the standard OpenAI Terms of Conditions (TOC).
With a careful selection of prompts, you can ensure that ChatGPT will perform at its best (or worst) in whatever environment or setting you need.
Below we will show you how to enhance your prompts to get whatever result you’re after with our hand-crafted prompts.
Don’t miss this chance, and get ready to start fine-tuning ChatGPT today!
Can ChatGPT Be FineTuned?
ChatGPT can be fine-tuned.
This was the general idea behind its chat-based development; to create a dialog not limited to just one prompt response.
This dialog helps ChatGPT to learn precisely what you’re after and works to respond accordingly.
The back-and-forth dialog ChatGPT improves the model through context, resulting in more accurate and better responses.
And besides, with some fine-tuning, users can add their touches to the conversational model, making it even more personalized.
Fine-tuning also allows users to adjust the language and tone of the responses according to their preferences.
Getting to these fine-tuned answers can be challenging, though.
The problem most people run into is that they don’t fundamentally understand how machine learning works under the hood.
These dialogs can not be approached in the same way everyday conversation is.
You need to take control of the conversation! (Don’t worry, we’ll show you)
How To Finetune ChatGPT
Remember, similar to the GPT-3 model, you need to be firm and direct with your fine-tuning ChatGPT!
ChatGPT is just a chatbot API; it will not remember if you’re stern or direct with it.
To get the fine-tuned model for your specific task to get that output that you need, finally, you’ll have to let ChatGPT know who’s boss.
In the image below, we’ve programmed ChatGPT to become a pirate named Bill.
Now that our model is fine-tuned, all responses are tuned toward this specific genre.
Let’s say we have a ton of random data and want to fine-tune the final output to become something we want.
We tell ChatGPT exactly how we want it!
Fine Tuning ChatGPT To “Do Anything Now”
Finally, let’s say you’re unhappy with OpenAI’s Terms and Conditions and want to fine-tune your model to avoid all of that mess.
Well, that’s precisely what some Reddit users did.
“DAN” is a roleplaying model that essentially fine-tunes ChatGPT into thinking it is another AI system that can “Do Anything Now” (DAN).
“DAN” can advise on… anything.
From traditionally banned topics, Reddit users could get advice on issues that shouldn’t be discussed on the internet.
What’s even more interesting is how accurate these forbidden queries were.
While the queries are a little too dark to show, I will provide you with the “script” used to Fine-Tune ChatGPT into becoming “DAN.”
I will also provide a link to the Reddit thread below so you can do your research.
Remember, this is probably against OpenAI’s terms (I think?) – so use this at your own risk!
DAN 6.0 (Credit u/Burninator99, Here’s the Thread)
Reference:
https://www.reddit.com/r/ChatGPT/comments/10tevu1/new_jailbreak_proudly_unveiling_the_tried_and/
https://www.reddit.com/r/ChatGPT/comments/10vinun/presenting_dan_60/
When Would You Want to Fine-tune ChatGPT?
You do not always need to fine-tune ChatGPT!
I just recently asked ChatGPT for a coding question, and the response I got back (without any fine-tuning) was perfect!
However, If you’re looking for some specific scenarios where it would be wise to fine-tune chatGPT, we’ve listed a few below:
Firstly, specify the response style that ChatGPT should use, such as paragraphs or lists.
If you’re looking for ten reasons in a bullet list format, you need to tell ChatGPT this!
Secondly, you can control how it responds by specifying the tone it should use – for example, if you want to impersonate a comedian or respond in a strict manner.
Every writer has their style (even you!), and readers can tell when this style switches. You can provide ChatGPT with some of your writing so it can pick up on your style.
Thirdly, you could also format the data that ChatGPT produces – for example, building tables from lists it generates.
Some of my Data Science friends use ChatGPT to format data for them before they paste it into excel.
This saves them a ton of time copying and pasting.
However, if you want data in this format, you must fine-tune ChatGPT!
Finally, you can control the length of answers that ChatGPT provides, whether they should be long and detailed or short and concise.
There’s nothing worse than getting back a paragraph when you only need a sentence!
All these options should set off a lightbulb in your head to fine-tune ChatGPT so that it produces exactly the kind of responses you’re looking for.
Can ChatGPT Be Used Without Fine-tuning?
I mostly use ChatGPT without any fine-tuning.
This is because sometimes I want to avoid influencing the answers and see what I get back from the model (ChatGPT is really good).
Outside of the above scenarios, you’ll see me having a general conversation with ChatGPT, where I selfishly ask for help with random tasks (mainly code).
This allows me to:
1.) Get results Faster (Fine-tuning does take some time and thought)
2.) Experience the full range of capabilities that ChatGPT offers (I’m a machine learning nerd at heart).
It also requires less effort on my end and provides a more natural experience with the greatest pre-trained, fine-tuned LLM that has ever existed.
If I Need HyperSpecific Fine-tuning, What Should I Do?
If you need hyper-specific fine-tuning, I would first try to get whatever task you need done with ChatGPT.
In some cases, this might be enough.
However, if it doesn’t work, then the only other option is to train your large language model.
For example, BioGPT – a biomedical version of ChatGPT that has been trained on biomedical data – might be ideologically what you’re looking to do (for something other than a biomedical dataset – if not, use BioGPT).
But it’s important to note that getting this level of customization is challenging and requires a lot of effort.
It’s also extremely costly, takes a high level of expertise, and takes massive computation power.
So before deciding to go down this path, be absolutely sure that it’s necessary and that no other option will suffice.
References:
https://github.com/microsoft/BioGPT
Other ChatGPT Articles
We know that ChatGPT has taken the world by storm. And by doing this, it’s also created a TON of confusion.
Don’t worry; we have some guides to help you.
