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Copy file name to clipboardExpand all lines: source/en/user_guide/internnav/quick_start/installation.md
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Currently the gradio demo is only available in **habitat** environment. Replace the 'model_path' variable in 'vln_gradio_backend.py' with the path of InternVLA-N1 checkpoint.
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```bash
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conda activate <habitat-env>
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python3 scripts/eval/vln_gradio_backend.py
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python3 scripts/demo/vln_gradio_backend.py
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```
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Find the IP address of the node allocated by Slurm. Then change the BACKEND_URL in the gradio client (navigation_ui.py) to the server's IP address. Start the gradio.
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```bash
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python scripts/eval/navigation_ui.py
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python scripts/demo/navigation_ui.py
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```
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Note that it's better to run the Gradio client on a machine with a graphical user interface (GUI) but ensure there is proper network connectivity between the client and the server. Download the gradio scene assets from [huggingface](https://huggingface.co/datasets/InternRobotics/Scene-N1) and extract them into the `scene_assets` directory of the client. Then open a browser and enter the Gradio address (such as http://0.0.0.0:5700). We can see the interface as shown below.
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