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--- |
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title: "POSEIDON Multiscience Demo" |
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emoji: "🔱" |
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colorFrom: "blue" |
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colorTo: "pink" |
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sdk: gradio |
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sdk_version: "4.29.0" |
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app_file: app.py |
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pinned: false |
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--- |
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# 🔱 POSEIDON Playground: Across Scientific Domains 🔱 |
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**An interactive Gradio demo** exploring how the POSEIDON foundation model for solving Partial Differential Equations (PDEs) could be applied across physics, finance, quantum mechanics, and biology. |
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> Built with love 💖 🔱 for the Hugging Face Community ML Research Engineer take-home assignment. |
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> Inspired by [POSEIDON: A Foundation Model for Solving PDEs](https://arxiv.org/abs/2405.19101) by CamLab ETH Zürich. |
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> Code from the original repo: [github.com/camlab-ethz/poseidon](https://github.com/camlab-ethz/poseidon) |
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--- |
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## Goal |
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This app highlights the **multidisciplinary potential** of pre-trained PDE models like POSEIDON using: |
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- Intuitive **interactive visualizations** |
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- Simple simulations from **four real-world domains** |
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## 🪩 What You Can Do |
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| Feature | Description | |
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|-----------|-------------| |
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| ✔️ Pick a scientific domain | Finance, Quantum, Fluids, Biology | |
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| ✔️ Run a mini simulation | See how PDEs behave in each field | |
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| ✔️ Try POSEIDON inference | Generate predictions from synthetic inputs | |
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| ✔️ Use real PDE datasets | Compare POSEIDON output vs. ground truth | |
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## 🚀 Running Locally |
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1. **Clone this repo** |
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```bash |
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git clone https://github.com/YOUR_USERNAME/poseidon_demo.git |
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cd poseidon_demo |
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``` |
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2. **(Option A) Using Conda** |
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```bash |
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conda env create -f environment.yml |
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conda activate poseidon-demo |
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``` |
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3. **(Option B) Using virtualenv** |
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```bash |
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python -m venv .venv |
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source .venv/bin/activate |
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pip install -r requirements.txt |
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``` |
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4. **(Run the demo** |
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```bash |
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python -m poseidon_demo.app |
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``` |
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## 🪩 Big Thanks |
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- Hugging Face for the opportunity and open tools |
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- ETH Zürich’s CamLab for releasing the POSEIDON repo |
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- 💖 You, the curious science hacker, for playing with this demo! |
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