| # Deploy LoRA Studio To Your Own HF Space | |
| This guide deploys the full LoRA Studio UI to your own Hugging Face Space. | |
| For the dedicated Qwen captioning UI, see `docs/deploy/QWEN_SPACE.md`. | |
| ## Prerequisites | |
| - Hugging Face account | |
| - `HF_TOKEN` with repo write access | |
| - Python environment with `requirements.txt` installed | |
| ## Fast Path (Recommended) | |
| ```bash | |
| python scripts/hf_clone.py space --repo-id YOUR_USERNAME/YOUR_SPACE_NAME | |
| ``` | |
| Optional private Space: | |
| ```bash | |
| python scripts/hf_clone.py space --repo-id YOUR_USERNAME/YOUR_SPACE_NAME --private | |
| ``` | |
| ## Manual Path | |
| 1. Create a new Space on Hugging Face: | |
| - SDK: `Gradio` | |
| 2. Push this repo content (excluding local artifacts) to that Space repo. | |
| 3. Ensure README front matter has: | |
| - `sdk: gradio` | |
| - `app_file: app.py` | |
| 4. In Space settings: | |
| - select GPU hardware (A10G/A100/etc.) if needed | |
| - add secrets (`HF_TOKEN`) if your flow requires private Hub access | |
| ## Runtime Notes | |
| - Space output defaults to `/data/lora_output` on Hugging Face Spaces. | |
| - Enable persistent storage if you need checkpoint retention across restarts. | |
| - For long-running non-interactive training, HF Jobs may be more cost-efficient than keeping a Space running. | |