This demo is part of a series on fine-tuning AI models. Article availablehere
I strongly recommend reading the article to understand what is happening as the two versions of the model run. To see the full impact of the fine-tune, slide the Cringe factor to 5+ and compare the outputs.
Interactive Demo
This demo runs a fine-tuned model on a GPU that sleeps between uses. Click to activate — it may take ~60 seconds to warm up on first run.
This is a small model and probably due to the specific prompting, some of the outputs can be a little nonsensical. This is an experiment rather than a production-ready fine-tune. I will work to further to try and improve this. However, if we pay attention to the tone and intent of the posts rather than how it reads as a whole, there are some interesting patterns.
The Cringe Factor has the largest overall impact on the model outputs — you can see this changes the prompt quite significantly as you move the slide towards 10.
At a Cringe Factor of 1–2, the two posts sound different, but honestly either could read as a down-to-earth(ish) post you might see on LinkedIn. The key parts of the prompt are:
Transform mundane professional updates into LinkedIn posts. ... Refer to people by first name only, never as @Name. Write in a professional but enthusiastic tone.
By the time we get to 4, the models are diverging — and the base Gemma4-E2B is sounding increasingly unhinged. Here are the parts of the prompt that changed:
Transform mundane professional updates into LinkedIn posts. ... Write in an over-the-top enthusiastic tone. Heavy buzzwords. Multiple emojis. Treat this as a significant milestone and extract an unsolicited life lesson.
As you turn the Cringe Factor higher, the Base Gemma4-E2B model becomes almost ‘cartoon-villain-like’ in its responses — very over-the-top, often repeating phrases and using a very un-LinkedIn writing style. The fine-tuned model is pretty much sticking to the script and produces some very amusing outputs: a parody of a LinkedIn post. Here is the same part of the prompt at a 10:
Transform mundane professional updates into LinkedIn posts. ... Treat this mundane event as a profound turning point that changed everything. Unsolicited wisdom. Humble brags that aren’t humble. Include a dramatic pause. End with a rhetorical question or a call to action.
So you can see, the fine-tuning is taking effect, and increasingly so as we dial up the absurdity we want from our post.
Another interesting observation: the fine-tuned Gemma4-E2B will also apply the tropes (‘No one is talking about’, ‘Here’s the uncomfortable truth’, etc) in a more coherent, ‘LinkedIn’ way, suggesting it has learned the style and how to use those openers from its fine-tuning. The baseline Gemma4-E2B model does use them, but it feels far more clunky in how it applies them.