Stop 10 · NLP & Modern AITopics · 6/7
Pretrained LLMs & Fine-Tuning Basics
Part of the Data Science Roadmap
In short
Using an already-trained large language model (via an API or open weights) and adapting it to a specific task — often via fine-tuning or, more commonly today, careful prompting.
How to learn this
- 1Use a pretrained model (via Hugging Face or an API) for a simple text classification task.
- 2Learn the difference between full fine-tuning, parameter-efficient fine-tuning, and prompting.
- 3Understand why fine-tuning from scratch is rarely necessary for most practical tasks today.
More topics at this stop
Stuck on this topic? Ask an Insider
Get 1:1 guidance from people who've walked this exact path — on the InsideEdge app.
