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Merged
Tai-Wang merged 6 commits into from
Jan 5, 2026
Merged

Bump to v0.3.0 #218

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b654fbb
Bump version to 0.2.0
Tai-Wang Dec 8, 2025
c863bd7
bump version to 0.3.0
kew6688 Dec 30, 2025
abac598
Merge branch 'main' into bump_to_0.3.0
kew6688 Dec 30, 2025
00fc29c
add introduction for VLLN
kew6688 Dec 30, 2025
1c5c7c8
Update README.md
kew6688 Jan 5, 2026
400ed5b
Update release date for InternNav v0.3.0
kew6688 Jan 5, 2026
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2 changes: 2 additions & 0 deletions README.md
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Expand Up @@ -37,6 +37,8 @@ The toolbox supports the most advanced high-quality navigation dataset, InternDa
## 🔥 News
| Time | Update |
|---------|--------|
| 2025/12 | InternNav v0.3.0 released. |
| 2025/12 | We introduce Interactive Instance Goal Navigation (IIGN) and release VL-LN Bench to enable InternVLA-N1 to solve this task, with large-scale dialog-trajectory collection plus training and evaluation support. See [our website](https://0309hws.github.io/VL-LN.github.io/) for details.|
| 2025/12 | Training code for InternVLA-N1 is now available. This release provides two model configurations: InternVLA-N1 (Dual System)<span style="color: #28a745; font-size: 0.9em"> with NavDP*</span> and InternVLA-N1 (Dual System)<span style="color: #28a745; font-size: 0.9em"> DualVLN </span>. For model architecture and training details, please refer to the [DualVLN paper](https://arxiv.org/abs/2512.08186).|
| 2025/11 | InternNav v0.2.0 released — added distributed evaluation support for VLN-PE.|
| 2025/10 | Add a [inference-only demo](scripts/notebooks/inference_only_demo.ipynb) of InternVLA-N1. |
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7 changes: 1 addition & 6 deletions setup.py
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Expand Up @@ -55,7 +55,7 @@ def parse_readme(readme: str) -> str:

setuptools.setup(
name='internnav',
version='0.2.0',
version='0.3.0',
packages=setuptools.find_packages(),
author='Intern Robotics',
author_email='embodiedai@pjlab.org.cn',
Expand All @@ -78,11 +78,6 @@ def parse_readme(readme: str) -> str:
# envs
"isaac": isaac_requires,
"habitat": habitat_requires,
"demo": [
"gradio==5.45",
"hf-xet==1.1.5",
"huggingface-hub==0.33.4",
],
# models
"internvla_n1": n1_requires,
"baseline": model_requires,
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