| --- |
| title: ArabGuard Egyptian |
| emoji: 🛡️ |
| colorFrom: green |
| colorTo: blue |
| sdk: docker |
| app_port: 7860 |
| pinned: false |
| --- |
| |
| # ArabGuard Egyptian |
|
|
| This Docker Space trains the classifier during the image build from the public |
| [`d12o6aa/ArabGuard-Egyptian-V1`](https://huggingface.co/datasets/d12o6aa/ArabGuard-Egyptian-V1) |
| dataset, then serves the trained model through Streamlit. |
|
|
| Only the source code, dependency lock, and Docker configuration belong in the |
| Space repository. Model weights, checkpoints, downloaded datasets, caches, and |
| dashboard outputs are generated during the Docker build and are ignored by Git. |
|
|
| The first build can take a long time because `xlm-roberta-base` is trained on CPU. |
| The Dockerfile uses a separate training stage, so downloaded data, Hugging Face |
| caches, optimizer states, and checkpoints are not copied into the runtime image. |
| Changing only `app.py` reuses the cached training layer when Docker cache is |
| available; changing `train_model.py`, `requirements.txt`, or an earlier layer |
| starts training again. |
|
|
| ## Space repository contents |
|
|
| Upload only: |
|
|
| - `.dockerignore` |
| - `.gitignore` |
| - `Dockerfile` |
| - `README.md` |
| - `app.py` |
| - `requirements.txt` |
| - `train_model.py` |
|
|
| Do not upload `.venv`, model weights, checkpoints, dataset files, caches, or |
| `dashboard_data`. |
|
|
| Before pushing, check the staged file list and sizes: |
|
|
| ```bash |
| git status --short |
| git ls-files |
| ``` |
|
|
| The Space listens on port `7860`, as required by the `app_port` metadata above. |
|
|
