Robotics
Transformers
Safetensors
qwen2_5_vl
text-generation
vision-language-model
video-language-model
navigation
text-generation-inference
Instructions to use InternRobotics/InternVLA-N1-wo-dagger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InternRobotics/InternVLA-N1-wo-dagger with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForCausalLM processor = AutoProcessor.from_pretrained("InternRobotics/InternVLA-N1-wo-dagger") model = AutoModelForCausalLM.from_pretrained("InternRobotics/InternVLA-N1-wo-dagger", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update model card: Add main paper link, update project page and citation
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by nielsr HF Staff - opened
README.md
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pipeline_tag: robotics
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library_name: transformers
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license: cc-by-nc-sa-4.0
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tags:
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# InternVLA-N1: An Open Dual-System Navigation Foundation Model with Learned Latent Plans
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Project
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Data: https://huggingface.co/datasets/InternRobotics/InternData-N1
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* We recommend using this official release for research and deployment, as it contains the most stable and up-to-date improvements.
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### Key Difference: Preview vs Official
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| System Design | Dual-System (synchronous)
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| Training
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## Highlights
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If you find our work helpful, please consider starring this repo 🌟 and cite:
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```bibtex
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```
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library_name: transformers
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license: cc-by-nc-sa-4.0
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pipeline_tag: robotics
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tags:
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- vision-language-model
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- video-language-model
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- navigation
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<div id="top" align="center">
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</div>
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# InternVLA-N1: An Open Dual-System Navigation Foundation Model with Learned Latent Plans
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**Paper:** [Ground Slow, Move Fast: A Dual-System Foundation Model for Generalizable Vision-and-Language Navigation](https://huggingface.co/papers/2512.08186)
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**Code:** [](https://github.com/InternRobotics/InternNav)
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**Project Page:** https://internrobotics.github.io/internvla-n1-dualvln.github.io/
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**Technical Report (InternVLA-N1):** https://internrobotics.github.io/internvla-n1.github.io/static/pdfs/InternVLA_N1.pdf
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**Data:** https://huggingface.co/datasets/InternRobotics/InternData-N1
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* We recommend using this official release for research and deployment, as it contains the most stable and up-to-date improvements.
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### Key Difference: Preview vs Official
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| Feature | InternVLA-N1-Preview | InternVLA-N1 (official) |
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| System Design | Dual-System (synchronous) | Dual-System (asynchronous) |
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| Training | System 1 trained only at System 2 inferrence step | System 1 trained on denser step (~25 cm), using latest System 2 hidden state |
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| Inference | System 1, 2 infered at same frequency (~2 hz) | System 1, 2 infered asynchronously, allowing dynamic obstacle avoidance |
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| Performance | Solid baseline in simulation & benchmarks | Improved smoothness, efficiency, and real-world zero-shot generalization |
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| Status | Historical preview | Stable official release (recommended)
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## Highlights
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If you find our work helpful, please consider starring this repo 🌟 and cite:
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```bibtex
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@article{wei2025ground,
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title={Ground Slow, Move Fast: A Dual-System Foundation Model for Generalizable Vision-and-Language Navigation},
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author={Wei, Meng and Wan, Chenyang and Peng, Jiaqi and Yu, Xiqian and Yang, Yuqiang and Feng, Delin and Cai, Wenzhe and Zhu, Chenming and Wang, Tai and Pang, Jiangmiao and Liu, Xihui},
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journal={arXiv preprint arXiv:2512.08186},
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year={2025}
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}
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```
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