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docs: improve assets (#2777)

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* add assets

* add libero results pifast:

* update

* update

* update size

* update naems:
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* update training tokenizer
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Jade Choghari
2026-01-12 13:33:28 +01:00
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parent 91ff9c4975
commit 473f1bd0e0
8 changed files with 129 additions and 7 deletions
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docs/source/groot.mdx
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@@ -12,6 +12,12 @@ Developers and researchers can post-train GR00T N1.5 with their own real or synt
GR00T N1.5 (specifically the GR00T-N1.5-3B model) is built using pre-trained vision and language encoders. It utilizes a flow matching action transformer to model a chunk of actions, conditioned on vision, language, and proprioception.
<img
src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/lerobot/lerobot-groot-paper1%20(1).png"
alt="An overview of GR00T"
width="80%"
/>
Its strong performance comes from being trained on an expansive and diverse humanoid dataset, which includes:
- Real captured data from robots.