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AIRO-Doffy-WRM-Grasp-consensus-two-contact-mlp-fixed-equal-lambda01
IXDLI/AIRO-Doffy-WRM-Grasp-consensus-two-contact-mlp-fixed-equal-lambda01
AIRO-Doffy-WRM-Grasp-consensus-two-contact-mlp-fixed-equal-lambda01 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.
Fixed-equal two-expert WRM policy-consensus Diffusion Policy checkpoint.
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Updated Sep 14, 2026
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25.2 GB
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.pt25.2 GB · 100%
At a glance
- Task
- Robotics
- Library
- pytorch
- Access
- Public
- Created
- Sep 14, 2026
- Updated
- Sep 14, 2026
- SHA
- 2553af74
Model card
From the Hugging Face model README
AIRO-Doffy-WRM-Grasp-consensus-two-contact-mlp-fixed-equal-lambda01
Fixed-equal two-expert WRM policy-consensus Diffusion Policy checkpoint.
- Experts: exactly two jointly trained experts, BEAVER (both rings) and vision.
- BEAVER encoder:
contact_mlp, using the configured contact representation. - Fusion:
fixed_equaluses invariant weights 0.5/0.5 for both training and inference. Each denoising step fuses the two epsilon predictions as0.5 * epsilon_beaver + 0.5 * epsilon_vis. - Expert auxiliary loss weight (
lambda_expert): 0.1. - Seed: 42; batch size: 32; final training step: 100000.
- Artifacts:
checkpoints/contains the numbered consensus checkpoints,last.pt, the resolved configuration, and metrics. Source and provenance files are included only when present in the explicit allowlist. - SHA-256 of
checkpoints/last.pt: d72ba09c1e6e549571cf520c3f7db0d882ed9841463c5533b2ed627153fdb0d1.
The run used online Weights & Biases (W&B) tracking. W&B run data and credentials are excluded from this repository.
- Task
- Robotics
- Library
- pytorch
- Created
- Sep 14, 2026
- Updated
- Sep 14, 2026