Robotics
Transformers
Safetensors
qwen3_vl
image-text-to-text
embodied-navigation
vision-language-navigation
visual-tracking
vision-language-action
qwen3-vl
Instructions to use LightOriginsHQ/LightNav-0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LightOriginsHQ/LightNav-0 with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("LightOriginsHQ/LightNav-0") model = AutoModelForMultimodalLM.from_pretrained("LightOriginsHQ/LightNav-0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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- Output: dual-channel pointing tokens (`<apos_*>` / `<opos_*>`) followed by three RVQ action
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tokens (`<act_l0_*><act_l1_*><act_l2_*>`) decoded to a 10-step waypoint chunk.
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## License
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Apache License 2.0.
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- Output: dual-channel pointing tokens (`<apos_*>` / `<opos_*>`) followed by three RVQ action
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tokens (`<act_l0_*><act_l1_*><act_l2_*>`) decoded to a 10-step waypoint chunk.
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## Community
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Questions, deployment notes and release news -join us on [Discord](https://discord.gg/zwZuD9JG), or scan to join the WeChat group.
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## License
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Apache License 2.0.
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