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---
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.
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