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.
Fuente del modelo
- Tipo
- Other
- Tamaño del archivo
- 7,37 KB–197 MB
- Versión
- vRevision 1774a1c
- Actualizado
- 22 sept 2026
- Descargas
- 3
- Fuente
- Hugging Face
Extracto de la fuente
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
Fuentes
1 fuenteVerificado 22 sept
Artefactos del modelo
3 artefactos
Artefactos del modelo
3 artefactosExtractos de fuentes
2 extractos
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
