🐦 PigeonAIModel1

This is a simple text classification model trained to detect whether an input sentence is positive (good) or negative (bad), based on labeled examples of common good and bad expressions.

🧠 How it works

• Fine-tuned on a synthetic dataset of 1000 labeled sentences.
• Uses distilbert-base-uncased architecture from Hugging Face Transformers.

🧪 Example Usage

from transformers import pipeline

classifier = pipeline("text-classification", model="tapigeon/PigeonAIModel1")
print(classifier("You are amazing!"))      # → Good
print(classifier("You're so stupid!"))     # → Bad