README.md

metadata

title: Simple Text Classifier
emoji: 📰
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 6.24.0
app_file: app.py
pinned: false
license: mit
short_description: Classifies news into World, Sports, Business, or Sci/Tech.

My first MLOps Project

🚧 Currently just started to learn MLOps (how to build and deploy models) — following the Made With ML course.

📊 Using one of the public datasets on Hugging Face, fancyzhx/ag_news, to classify news headlines into World, Sports, Business, or Sci/Tech.

🚀 Live demo: huggingface.co/spaces/Evasim/Simple-Text-Classifier

🤗 Trained model: huggingface.co/Evasim/First_Project (fine-tuned SciBERT)

Reproducing locally

git clone https://github.com/evasim/my-first-MLOPS-project.git
cd my-first-MLOPS-project
pip install -r requirements.txt

# regenerate the dataset (not committed — it's public and regenerable)
python src/data_ingestion.py

# run the test suite
pytest src/

To run predictions against the trained model, add to a .env file:

HF_REPO_ID=Evasim/First_Project

Then: python -m src.predict "your headline here"

Training happens in notebooks/MLOPS_project.ipynb.