---
title: Cheese Texture (Tabular) — AutoGluon Gradio App
emoji: 🧀
colorFrom: yellow
colorTo: blue
sdk: gradio
sdk_version: "4.44.0"
app_file: app.py
pinned: false
---

# Cheese Texture (Tabular) — Gradio App

Predicts **texture** from nutritional/origin features using a **classmate's AutoGluon model**.

- **Model (classmate):** [rlogh/cheese-texture-autogluon-classifier](https://huggingface.co/rlogh/cheese-texture-autogluon-classifier)  
- **Original dataset:** [aslan-ng/cheese-tabular](https://huggingface.co/datasets/aslan-ng/cheese-tabular)

## How to use
1. Set **fat**, **price**, **protein**, **origin**, and **holed**.  
2. Choose inference parameters (base model, output mode, Top‑k).  
3. View **Predicted texture**, **probability table**, and a **summary** of your input + results.

## Notes
- Sliders are constrained to dataset‑observed ranges.  
- Inputs are validated and friendly warnings are shown when we auto‑correct values.  
- This app uses AutoGluon's `TabularPredictor` for inference.

## Credits
- Model: rlogh (classmate)  
- Dataset: aslan-ng

## Citations
- Model: rlogh/cheese-texture-autogluon-classifier (Hugging Face model card)
- Dataset: aslan-ng/cheese-tabular (Hugging Face dataset card, MIT license)

## License
- MIT

## Acknowledgments
- Thanks to rlogh for the trained AutoGluon model and to aslan-ng for the dataset.
- Collaboration & GenAI usage: This submission was prepared with peer feedback and limited use of generative AI (ChatGPT) for packaging/refactoring and documentation polish.