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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.

TipoOtherVersiónRevision 1774a1cDcalidad

Fuente del modelo

Tipo
Other
Tamaño del archivo
7,37 KB–197 MB
Versión
vRevision 1774a1c
Actualizado
22 sept 2026
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3
Fuente
Hugging Face

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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.

Fuentes

1 fuente
Hugging FacePrincipalVersión 1774a1c6621c5899c34aa4826a162e91617e53e9
huggingface.co/JunJunJunya/bluecube_101_merged_policy_baseline/tree/1774a1c6621c5899c34aa4826a162e91617e53e9

Verificado 22 sept

Artefactos del modelo

3 artefactos

model.safetensors

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

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policy_postprocessor_step_0_unnormalizer_processor.safetensors

safetensors · 7,37 KB · SHA-256 7749e85e0c4b…767a · Hugging Face

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policy_preprocessor_step_3_normalizer_processor.safetensors

safetensors · 7,38 KB · SHA-256 61bb1b91cd80…8a8c · Hugging Face

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Extractos de fuentes

2 extractos

--- 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