---
license: apache-2.0
language: en
tags:
- text-classification
- distilbert
- linkedin
- slop
- humor
metrics:
- accuracy
- f1
base_model:
- distilbert/distilbert-base-uncased
---

# ⏱️SlopMeter

<div align="center">
  <img src="https://readme-typing-svg.demolab.com?font=Fira+Code&pause=1200&center=true&vCenter=true&width=640&lines=Passionate+results-driven+visionary...;Leveraging+synergies+to+drive+transformative+growth...;Thought+leader.+Disruptor.+Dog+lover.;Verdict%3A+SLOP" alt="Typing animation of slop LinkedIn bios">
</div>

Paste your LinkedIn bio. Find out how much it says about nothing.

<div align="center">
  <img src="https://api.memegen.link/images/drake/Software_Engineer/Visionary_Thought_Leader_Leveraging_Synergies.png" alt="Drake meme: Software Engineer vs Visionary Thought Leader" width="350">
</div>

<div align="center">
  <img src="https://img.shields.io/badge/license-Apache_2.0-blue" alt="License">
  <img src="https://img.shields.io/badge/base-distilbert--base--uncased-orange" alt="Base model">
  <img src="https://img.shields.io/badge/task-slop_detection-red" alt="Task">
  <img src="https://img.shields.io/badge/validation_loss-0.000007-brightgreen" alt="Validation loss">
  <img src="https://img.shields.io/badge/accuracy-suspiciously_high-yellow" alt="Accuracy">
  <img src="https://img.shields.io/badge/synergy-leveraged-lightgrey" alt="Synergy">
</div>

---

<div style="border-left: 4px solid #3b82f6; background: rgba(59, 130, 246, 0.12); padding: 10px 14px; border-radius: 6px; margin: 16px 0;">
  <b>🧪 Experimental, made for fun.</b> This is a joke model and not meant to shame anyone. It roasts buzzwords, not people. The roasts are canned lines from a fixed list, not learned from anyone's real profile. It has no connection to LinkedIn and shouldn't be used for hiring or judging anyone.
</div>

---

A fine-tuned `distilbert-base-uncased` that labels text `USEFUL` or `SLOP`, plus a small rule-based script that insults you about it. Trained on about 6,000 examples: tech tutorials, real job descriptions, and a lot of corporate cringe.

---

## Usage

```python
from transformers import pipeline

classifier = pipeline("text-classification", model="QuantaSparkLabs/BioSlopMeter")

text = "I am a passionate, results-driven visionary leveraging cutting-edge AI to drive transformative growth."
print(classifier(text))
# [{'label': 'SLOP', 'score': 0.9998}]
```
---

## Examples

**Input:** "I am thrilled to announce that I have accepted a new position as Chief Synergy Officer! Let's leverage our collective potential to drive transformative growth."

**Verdict:** SLOP (98%)
**Buzzwords:** leverage, synergy, transformative
**Roast:** You sound like a walking press release. This is vague enough to describe a bakery or a spaceship.

**Input:** "Compress images before uploading. Use WebP format. Enable browser caching."

**Verdict:** USEFUL (8%)
**Roast:** Actually useful. Weird. Take my upvote.

---

## How it works

DistilBERT does the classification. A few regex checks count buzzwords, numbers/tools mentioned, and action verbs. If the buzzword score is high and the action score is low, you get a random roast from a list.

## About the numbers

Validation loss is 0.000007. Yes, that's suspiciously low. The training data is easy to separate, so please don't treat this as a real benchmark. It will probably still roast your bio correctly, though.

## ⚠️Disclaimer

If your bio gets a 100% slop score, please don't send me a connection request. I won't accept it (I don't even have a profile).

Built in one evening because I wanted to roast LinkedIn bios without logging in. 🥀

> Experimental Model-2026