Download robocoin_multitask_mm/README.md from PoopBear/RIFT: direct link, hf CLI and curl.
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https://huggingface.co/PoopBear/RIFT/resolve/main/robocoin_multitask_mm/README.md
- Command line
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hf download hf://PoopBear/RIFT/robocoin_multitask_mm/README.md
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curl -L -o README.md https://huggingface.co/PoopBear/RIFT/resolve/main/robocoin_multitask_mm/README.md
RoboCOIN RIFT inference
Existing final RIFT checkpoint from 10 epochs / 9,340 optimizer steps on object classification (191 episodes), red/yellow test-tube mixing (50), and basket stacking (101). Original source provenance is in checkpoint_manifest.json.
hf download PoopBear/RIFT --include 'robocoin_multitask_mm/rift_10ep/*' 'assets/*' --local-dir ./checkpoints
export DIFFSYNTH_MODEL_BASE_PATH=./checkpoints/assets
Load ./checkpoints/robocoin_multitask_mm/rift_10ep/rift_step009340.pt with the adjacent
config.yaml and dataset_stats.json. The checkpoint includes anticipation/probe
parameters; preserve all model state and the packaged processor settings. For full
RIFT checkpoint loading, skip separate pretrained video/ActionDiT initialization
(skip_dit_load_from_pretrain=true, action_dit_pretrained_path=null) and enable
load_text_encoder=true for uncached prompts. Use weights_only=True for the policy
checkpoint. No raw dataset or training-view archive is needed for live inference.
Observation and action contract
- Policy action and proprioceptive state order is
[left_arm (6), left_gripper (1), right_arm (6), right_gripper (1)](14 values). The raw dataset's packed order is[left_arm (6), right_arm (6), left_gripper (1), right_gripper (1)]; reorder by named fields before policy preprocessing. - Arm joints remain in radians. When starting from the original RoboCOIN source
representations, multiply
classification and test-tube gripper values by
180/pito obtain the policy's millimeter convention; basket gripper values remain unchanged. Apply this to both actions and states, without clipping. Already-converted millimeter values must not be converted again. This conversion follows the original preprocessing's inverse degree-to-radian interpretation; per-subset export logs were not available. For a live robot, map its measured gripper units to the same policy convention, then invert that mapping when sending commands. - Cameras, in order:
head_rgb,left_wrist_rgb,right_wrist_rgb. Dataset aliases arecam_head_left_rgbfor classification/test-tube heads andcam_high_left_rgbfor basket heads; wrists arecam_left_wrist_rgbandcam_right_wrist_rgb. - Preserve the packaged 224 x 224 per-camera resizing, three-camera composition,
relative-joint transform for both arms, stepwise action normalization, and gripper
action normalization
0/100. Use this checkpoint's statistics for normalization and inverse action processing; do not substitute another dataset's statistics.
The saved config retains loader-compatible fields and original architecture settings.
Its normalization path points to the packaged statistics under ./checkpoints/;
relative paths resolve from the working directory. Dataset/cache/output fields are
retained metadata rather than inference setup instructions.