Ir para o conteúdo
ModelListadosExterno
Baixar

J Duck

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.

TipoOtherVersãoRevision e33d0ffDnota

Fonte do modelo

Tipo
Other
Tamanho do arquivo
7,41 KB–197 MB
Versão
vRevision e33d0ff
Atualizado
26 de set. de 2026
Downloads
38
Fonte
Hugging Face

Trecho da fonte

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.

Fontes

1 fonte
Hugging FacePrimárioVersão e33d0ff2f5b36ad9f635f7cad591bdc6efc73a57
huggingface.co/J-Hua/j_duck/tree/e33d0ff2f5b36ad9f635f7cad591bdc6efc73a57

Verificado 7 de ago.

Artefatos de modelo

3 artefatos

model.safetensors

safetensors · 197 MB · SHA-256 4920180ce39b…75e8 · Hugging Face

Baixar

policy_postprocessor_step_0_unnormalizer_processor.safetensors

safetensors · 7,41 KB · SHA-256 56523a9102c7…aa13 · Hugging Face

Baixar

policy_preprocessor_step_3_normalizer_processor.safetensors

safetensors · 7,42 KB · SHA-256 50ef49bf6b9c…702d · Hugging Face

Baixar

Trechos de fonte

2 trechos

--- datasets: NLTuan/j_duck library_name: lerobot license: apache-2.0 model_name: act pipeline_tag: robotics tags: - act - lerobot - robotics --- # 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:** `camera1`, `camera2` ## Inputs & Outputs The policy consumes these observation features and produces these action features. **Inputs** | Feature | Type | Shape | | --- | --- | --- | | `observation.state` | STATE | `(6,)` | | `observation.images.camera1` | VISUAL | `(3, 240, 320)` | | `observation.images.camera2` | VISUAL | `(3, 240, 320)` | **Outputs** | Feature | Type | Shape | | --- | --- | --- | | `action` | ACTION | `(6,)` | ## Training Dataset - **Repository:** [NLTuan/j_duck](https://huggingface.co/datasets/NLTuan/j_duck) - **Episodes:** 50 - **Frames:** 29546 - **Frame rate:** 30 FPS - **Task(s):** "pick and place duck" <a class="flex" href="https://huggingface.co/spaces/lerobot/visualize_dataset?path=NLTuan/j_duck"> <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 | 20000 | | Batch size | 32 | | Optimizer | adamw | | Learning rate | 3e-05 | | Seed | 1000 | | LeRobot version | 0.6.1 | --- ## How to Get Started...

Source context: 38 downloads · 0 likes · Pipeline robotics · Library lerobot · Repo J-Hua/j_duck