GraphAttributeLearning / README_SPACE.md
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Add Gradio app for inference and model selection
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## Hugging Face Space Setup
### 1. Prepare Repository
Push this project (including `app.py`, `requirements-space.txt`, and checkpoints) to a Git repository that you will connect to your Space.
Recommended checkpoint locations:
- Baseline: `outputs/smoke_baseline/best.pt`
- GNN: `outputs/smoke_gnn/best.pt`
### 2. Create a New Space
1. On Hugging Face, create a new **Space**.
2. Select **Gradio** as the SDK.
3. Point the Space to this repository (or upload the files manually).
### 3. Configure Runtime
- Hardware: start with **CPU**; upgrade to GPU if needed.
- Python dependencies:
- Set the Space to use `requirements-space.txt` as the dependency file.
### 4. Local Test Before Pushing
Create and activate a clean virtualenv, then run:
```bash
pip install -r requirements-space.txt
python app.py
```
Open the printed URL in your browser, upload a chair image, and verify that:
- Baseline and GNN models both run.
- Switching model type updates which checkpoint is used.
### 5. Expected Behavior in the Space
- The app starts from `app.py`.
- Default checkpoint paths:
- Baseline: `outputs/smoke_baseline/best.pt`
- GNN: `outputs/smoke_gnn/best.pt`
- You can override checkpoint paths via the text box in the UI.