kiteml / dual-openyam-close-box-act

huggingface.co
Total runs: 20
24-hour runs: 1
7-day runs: 20
30-day runs: 20
Model's Last Updated: September 28 2026
robotics

Introduction of dual-openyam-close-box-act

Model Details of dual-openyam-close-box-act

ACT · dual OpenYAM, "close the box"

A ACT policy for a bimanual OpenYAM robot, trained on kiteml/dual-openyam-close-box to close the box . ACT is Action Chunking with Transformers: a conditional-VAE transformer that predicts chunks of future actions. Trained from scratch.

Trained with Kite on LeRobot v0.6.0.

Training
Dataset kiteml/dual-openyam-close-box : 31 episodes, 33,247 frames at 30 fps
Initialization none (from scratch)
Trained all parameters (ResNet-18 backbone initialized from ImageNet)
Steps 30,000
Batch size 8
Optimizer AdamW, lr 1e-5
Final training loss 0.102
Hardware 1× NVIDIA A100 40GB
Inputs and outputs
Feature Shape Contents
observation.images.top 3×480×640 top camera, RGB
observation.images.left_wrist 3×480×640 left wrist camera, RGB
observation.images.right_wrist 3×480×640 right wrist camera, RGB
observation.state 14 left arm joints 1–6, right arm joints 1–6, left gripper, right gripper
action 14 same layout as observation.state

Each inference call predicts 100 actions (3.3 s at 30 fps) and executes them all.

Usage

Requires LeRobot v0.6.0 or later.

import torch
from lerobot.policies.factory import get_policy_class, make_pre_post_processors

repo_id = "kiteml/dual-openyam-close-box-act"
policy = get_policy_class("act").from_pretrained(repo_id)
preprocessor, postprocessor = make_pre_post_processors(policy.config, pretrained_path=repo_id)

# observation: the input features above, formatted like a LeRobotDataset frame
# (images as float tensors in [0, 1], channels first)
observation["task"] = "close the box"
with torch.inference_mode():
    action = postprocessor(policy.select_action(preprocessor(observation)))

To run it with LeRobot's CLI tools, pass --policy.path=kiteml/dual-openyam-close-box-act to lerobot-record or lerobot-eval .

Evaluation

Not evaluated yet. The loss above is the final training loss, and no rollouts on the robot or in simulation have been scored.

Other policies trained on this dataset

Diffusion Policy · π₀ · π₀.₅ · π₀-FAST · SmolVLA · VLA-JEPA · X-VLA

Runs of kiteml dual-openyam-close-box-act on huggingface.co

20
Total runs
1
24-hour runs
20
3-day runs
20
7-day runs
20
30-day runs

More Information About dual-openyam-close-box-act huggingface.co Model

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dual-openyam-close-box-act install

dual-openyam-close-box-act is an open source model from GitHub that offers a free installation service, and any user can find dual-openyam-close-box-act on GitHub to install. At the same time, huggingface.co provides the effect of dual-openyam-close-box-act install, users can directly use dual-openyam-close-box-act installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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Url of dual-openyam-close-box-act

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kiteml
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huggingface.co

Total runs: 11
Run Growth: 11
Growth Rate: 100.00%
Updated:September 28 2026