Instructions to use mair-robosyn/ACT_sim_mixer_operating_stage1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use mair-robosyn/ACT_sim_mixer_operating_stage1 with LeRobot:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
ACT_sim_mixer_operating_stage1 (checkpoint 003000)
ACT policy for the RoboSynChallenge simulation task mixer_operating.
This repository root is a complete LeRobot pretrained_model directory.
The layout is identical to the official RoboSynChallenge/ACT_sim_mixer_operating repository.
Files
| File | sha256 |
|---|---|
config.json |
fab118b518716c9fbe8e18a13fe21dba05dd6526a900590bdece1697de363eea |
model.safetensors |
e7421dae4b9944b996f194e6ef1afbe2ae27326ed50c73e3cf395ad9206db06d |
train_config.json |
b4cae62009a350605564e18ecabe1e6e69ba7f67e46c7137869c89f9d1ac227c |
train_config.json is the unmodified training record. It contains absolute paths of the training machine. The loader does not read these paths.
Model
- Architecture: ACT (LeRobot 0.3.3), ResNet18 backbone, dim_model 512, VAE on.
- Initialization: official checkpoint
RoboSynChallenge/ACT_sim_mixer_operating. - Fine-tuning: full parameters, lr 1e-6 (backbone 1e-6), batch size 8, 3000 steps, seed 1000.
- Data: official
cobotmagic_Sim_mixer_operating(LeRobot v2.1, 1000 episodes, 316000 frames). The data is not included here.
Input and output
observation.state,observation.qvel,observation.qf: float32, shape[14]each.observation.images.cam_high,cam_left_wrist,cam_right_wrist: float32, shape[3, 480, 640].action: float32, shape[14](two arms, 7 values each, joint space plus gripper).- Normalization: MEAN_STD for VISUAL, STATE, ACTION. Statistics are stored in
model.safetensors. chunk_size50,n_action_steps50,n_obs_steps1, no temporal ensembling.
Procedure: download and evaluate
- Download the repository root:
hf download mair-robosyn/ACT_sim_mixer_operating_stage1 --repo-type model --local-dir checkpoints/ACT_sim_mixer_operating_stage1/ - Run the official ACT evaluation from the RoboSynChallenge repository:
bash policy/act/eval.sh mixer_operating random checkpoints/ACT_sim_mixer_operating_stage1 0 --pytorch_device cuda --headless True
Results (team-internal, not organizer results)
mixer_operating/random, headless, max 500 steps, LeRobot 0.3.3, PyTorch 2.7.0+cu128, RTX 5090.- 50 episodes (seeds 240926–240931): 46/50 = 92%, mean 267.38 steps.
- Official initialization checkpoint, same protocol, 20 episodes: 17/20 = 85%.
Warning
These results come from our local runs. The organizers did not verify them.
Note: no network needed at load time
config.json sets pretrained_backbone_weights to null. The loader does not download torchvision ResNet18 ImageNet weights. All backbone weights come from model.safetensors. The weights are unchanged from earlier revisions.
Earlier revisions 5dffabefb1dde4c36b29ec28f94c66171f1e0ce1 and a9403db63292bac6188518416221ad968f9c2a2d set ResNet18_Weights.IMAGENET1K_V1. With those revisions, the loader needs network access or a cached resnet18-f37072fd.pth in $TORCH_HOME/hub/checkpoints/. The action output is identical in both cases (verified, max abs diff 0.0).
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