| --- |
| title: QuPrep |
| emoji: ⚛️ |
| colorFrom: blue |
| colorTo: purple |
| sdk: gradio |
| sdk_version: 6.10.0 |
| app_file: app.py |
| pinned: true |
| license: apache-2.0 |
| short_description: Convert classical datasets into quantum-circuit-ready format |
| --- |
| |
| # QuPrep — Quantum Data Preparation Demo |
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| Upload a CSV (or use a built-in sample), pick an encoding and export framework, |
| and get a quantum circuit back — all in the browser. |
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| **3 tabs:** |
| - **Convert** — encode your data and see the circuit output + cost estimate |
| - **Recommend** — get a dataset-aware encoding recommendation for your task |
| - **Compare** — side-by-side cost table for all 11 encoders |
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| 📦 `pip install quprep` · 📖 [docs.quprep.org](https://docs.quprep.org) · 💻 [github.com/quprep/quprep](https://github.com/quprep/quprep) |
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