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王昱凯HanqingWangAI
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[docs] Fix typos in evaluation on isaac sim section
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requirements.txt

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toml==0.10.2
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internutopia
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myst_parser
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pre-commit==4.2.0
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pydata-sphinx-theme
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sphinx==6.2.1
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sphinx_copybutton==0.5.2
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sphinx_markdown_tables==0.0.17
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toml==0.10.2

source/en/user_guide/internnav/quick_start/train_eval.md

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Then change the 'model_path' in the cfg file to the path of the InternVLA-N1 weights. Start the evaluation server:
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```bash
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INTERNUTOPIA_ASSETS_PATH=/path/to/InternUTopiaAssets MESA_GL_VERSION_OVERRIDE=4.6 python scripts/eval/eval.py --config scripts/eval/configs/h1_internvla_n1_cfg.py
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python -m internnav.agent.utils.server --config scripts/eval/configs/h1_internvla_n1_cfg.py
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```
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Finally, start the client:
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```bash
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python -m internnav.agent.utils.server --config scripts/eval/configs/h1_internvla_n1_cfg.py
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INTERNUTOPIA_ASSETS_PATH=/path/to/InternUTopiaAssets MESA_GL_VERSION_OVERRIDE=4.6 python scripts/eval/eval.py --config scripts/eval/configs/h1_internvla_n1_cfg.py
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```
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The evaluation results will be saved in the `eval_results.log` file in the output_dir of the config file. The whole evaluation process takes about 3 hours at RTX4090 platform.

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