Instructions to use Unskild/ACT-Pick with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use Unskild/ACT-Pick with LeRobot:
- Notebooks
- Google Colab
- Kaggle
File size: 899 Bytes
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library_name: pytorch
tags:
- robotics
- manipulation
- imitation-learning
- act
- lerobot
---
# ACT-Pick
ACT-Pick is an **Action Chunking Transformer (ACT)** policy trained using
**LeRobot** for a tabletop **object pickup task**.
## Model Details
- Policy Type: ACT
- Learning Method: Imitation Learning
- Framework: PyTorch
## Files
- `model.safetensors` — trained policy weights
- `config.json` — model configuration
- `policy_preprocessor.json` — observation normalization config
- `policy_preprocessor_step_3_normalizer_processor.safetensors` — observation normalizer
- `policy_postprocessor.json` — action unnormalization config
- `policy_postprocessor_step_0_unnormalizer_processor.safetensors` — action unnormalizer
- `train_config.json` — training configuration
## Usage
```bash
lerobot-eval \
--policy.repo_id=NEW_HF_USERNAME/ACT-Pick \
--policy.device=cuda
```
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