TULLUS/MolmoAct2-Think

robotics model by TULLUS

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MolmoAct2-Think extends MolmoAct2 with depth-token reasoning. Before producing an action, the model can predict a compact 10 x 10 discrete depth representation and condition the action expert on the resulting depth-aware VLM cache. This checkpoint is the post-trained, multi-embodiment depth-reasoning model. It is intended as a foundation checkpoint for further robot fine-tuning rather than as a ready-to-run policy for a single deployment setting. Use this checkpoint for further fine-tuning when the downstream policy should use depth reasoning. It contains the VLM, action expert, and depth-token weights, plus normalization metadata for the post-training mixture in normstats.json. This model card intentionally does not include direct policy inference code. For ready-to-run depth-reasoning inference, use the fine-tuned MolmoAct2-Think-LIBERO checkpoint. MolmoAct2 generate robot actions from visual observations and language instructions, but their behavior may vary across embodiments, environments, and hardware configurations. Users should…

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Model overview

TULLUS/MolmoAct2-Think is a robotics model repository published by TULLUS on Hugging Face. The source reports the transformers library.

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Model facts

Task: robotics
Library: transformers
Recent downloads (30 days): 0
Cumulative likes: 0
Hugging Face trending score: 0
Reported safetensors parameters: 5,447,439,152
Architecture: MolmoAct2ForConditionalGeneration
License: Not reported — check the model card
Access: Not gated by Hugging Face
Created: 2026-09-17T06:14:49.000Z
Last modified: 2026-09-17T06:14:49.000Z

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