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AIRO-Doffy-WRM-Grasp-consensus-two-contact-mlp-detached-router-lambda0
IXDLI/AIRO-Doffy-WRM-Grasp-consensus-two-contact-mlp-detached-router-lambda0
AIRO-Doffy-WRM-Grasp-consensus-two-contact-mlp-detached-router-lambda0 is a robotics model from IXDLI. Use it for the robotics task on the model card, and read the license before you ship it in a product. It is set up for pytorch.
Two jointly trained diffusion experts: BEAVER (both rings) and vision. The unified BEAVER encoder uses 144 strict-<10 mm contact bits plus 9 sensor-enable features. A contact is valid only for status 5 or 9, a finite…
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Updated Sep 11, 2026
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At a glance
- Task
- Robotics
- Library
- pytorch
- Access
- Public
- Created
- Sep 11, 2026
- Updated
- Sep 11, 2026
- SHA
- 4eaf7a3a
Model card
From the Hugging Face model README
AIRO-Doffy-WRM-Grasp-consensus-two-contact-mlp-detached-router-lambda0
Two jointly trained diffusion experts: BEAVER (both rings) and vision. The unified BEAVER encoder uses 144 strict-<10 mm contact bits plus 9 sensor-enable features. A contact is valid only for status 5 or 9, a finite distance >= 0, and the presence gate. The two native observations are independent inputs to a shared MLP. No GRU and no raw distances are used.
Observation-only routing uses detach(z_B), detach(z_V), and q; x_t and t are not router inputs. The expert auxiliary loss weight is lambda_expert=0.0. Single task: cluster9, 1 GPU, 8 CPUs, batch size 32, online W&B tracking. Training ends at 100000 steps. Artifacts and source are in checkpoints/. last.pt SHA-256: b96f0f6e1e1ab9f762f30da5af564905177bebbf94f59fe08a1420853f8329a7
- Task
- Robotics
- Library
- pytorch
- Created
- Sep 11, 2026
- Updated
- Sep 11, 2026