What should I learn first before I fine-tune?

I’m interested in making a fine-tuned model so I can quickly make high-quality flashcards that follow a very specific format. but I have zero fine-tuning experience, let alone programming skills.

I am currently learning the basics of Python, but I’m not sure if it would be enough to even train my first fine-tuned model. Will I have to learn machine learning fundamentals, deep learning basics, NLP, data preparation, and model fine-tuning first? Is there a simpler learning path? What do you recommend?

Also, I will eventually cover these topics as part of my education, so this isn’t all just for fine-tuning a model.

Thank you in advance for any guidance!

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Background knowledge will help you a lot. There are many small decisions that can make your project successful or not. If you are working on a project to explore, you can go explore, try, fail, and learn. Learning machine learning and deep learning basics will equip you with a great foundation. However, you can still do fine-tunning with openai. You should start reading this : Fine-tuning - OpenAI API

Also, there are some papers showing that in-context learning is often better than fine-tuning small models. So, you may want to work on the prompt engineering parts to see whether you can solve your problem with prompting.

Good luck!


You’ll learn what you need to know along the way. Read the finetuning documentation and stay curious. I finetuned 10 models before I got the outputs I wanted. Just know that actually finetuning will be about 10-20% of the work. Most of it it data gathering, cleaning, sorting, creating, etc.

But again, while it is possible to finetune a model to generate flashcards, this is a task that on-shelf models can complete with proper instruction and prompting.

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