Skip to content
ModelListedExternal
Download

Bluecube 101 Merged Policy Baseline

Action Chunking with Transformers (ACT) is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high success rates.

KindOtherVersionRevision 1774a1cDgrade

Model source

Kind
Other
File size
7.37 KB–197 MB
Version
vRevision 1774a1c
Updated
Sep 22, 2026
Downloads
3
Source
Hugging Face

Source excerpt

Action Chunking with Transformers (ACT) is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high success rates.

Sources

1 source
Hugging FacePrimaryVersion 1774a1c6621c5899c34aa4826a162e91617e53e9
huggingface.co/JunJunJunya/bluecube_101_merged_policy_baseline/tree/1774a1c6621c5899c34aa4826a162e91617e53e9

Verified Sep 22

Model artifacts

3 artifacts

model.safetensors

safetensors · 197 MB · SHA-256 56b9c45fba35…3e7d · Hugging Face

Download

policy_postprocessor_step_0_unnormalizer_processor.safetensors

safetensors · 7.37 KB · SHA-256 7749e85e0c4b…767a · Hugging Face

Download

policy_preprocessor_step_3_normalizer_processor.safetensors

safetensors · 7.38 KB · SHA-256 61bb1b91cd80…8a8c · Hugging Face

Download

Source excerpts

2 excerpts

--- datasets: JunJunJunya/bluecube_101_merged library_name: lerobot license: apache-2.0 model_name: act pipeline_tag: robotics tags: - act - robotics - lerobot --- # Model Card for act <!-- Provide a quick summary of what the model is/does. --> [Action Chunking with Transformers (ACT)](https://huggingface.co/papers/2304.13705) is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high success rates. <!-- A short demo is worth more than any description! Record a GIF/video of the policy running on your robot, upload it to this repo, and embed it here: <p align="center"> <img src="https://huggingface.co/<hf_user>/<policy_repo_id>/resolve/main/demo.gif" width="60%"/> </p> --> This policy has been trained and pushed to the Hub using [LeRobot](https://github.com/huggingface/lerobot). Learn how to train and run it in the [LeRobot act guide](https://huggingface.co/docs/lerobot/main/en/act), or browse the [full documentation](https://huggingface.co/docs/lerobot/index). --- ## Model Details - **License:** apache-2.0 - **Robot type:** `so_follower` - **Cameras:** `front`, `side` ## Inputs & Outputs The policy consumes these observation features and produces these action features. **Inputs** | Feature | Type | Shape | | --- | --- | --- | | `observation.state` | STATE | `(6,)` | | `observation.images.front` | VISUAL | `(3, 480, 640)` | | `observation.images.side` | VISUAL | `(3, 480, 640)` | **Outputs** | Feature | Type | Shape | | --- | --- | --- | | `action` | ACTION | `(6,)` | ## Training Dataset - **Repository:** [JunJunJunya/bluecube_101_merged](https://huggingface.co/datasets/JunJunJunya/bluecube_101_merged) - **Episodes:** 259 - **Frames:** 81146 - **Frame rate:** 30 FPS - **Task(s):** "Grab the blue cube", "Grab the blue cube and place in the hole" <a class="flex" href="https://huggingface.co/spaces/lerobot/visualize_dataset?path=JunJunJunya/bluecube_101_merged"> <img class="block dark:hidden" src="https://huggingface.co/datasets/huggingface/badges/resolve/main/visualize-this-dataset-xl.svg"/> <img class="hidden dark:block" src="https://huggingface.co/datasets/huggingface/badges/resolve/main/visualize-this-dataset-xl-dark.svg"/> </a> ## Training Configuration | Setting | Value | | --- | --- | | Training steps | 50000 | | Batch size | 16 | | Optimizer |...

Source context: 3 downloads · 0 likes · Pipeline robotics · Library lerobot · Repo JunJunJunya/bluecube_101_merged_policy_baseline