| --- |
| 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¢er=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 |
