Instructions to use AgathiKari/act_etiq_pick3_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use AgathiKari/act_etiq_pick3_v1 with LeRobot:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
ACT Policy for Tube Pick-and-Place
This is an Action Chunking with Transformers (ACT) policy trained with LeRobot on a custom dataset for picking up a tube and returning to the starting position.
Model Details
- Developed by: Your Name
- Model type: ACT (Action Chunking with Transformers)
- Language(s): English (task instruction)
- License: Apache 2.0
- Finetuned from: ACT (trained from scratch)
- Repository: YOUR_CORRECT_USERNAME/act_etiq_pick3_v1
Uses
Direct Use
This policy can be used with a SO-100 follower robot arm to perform the task: "Grasp the tube, lift it, place it back down, and return to the starting position."
Out-of-Scope Use
Not intended for other tasks or robot morphologies without retraining.
Training Details
Training Data
The model was trained on the YOUR_CORRECT_USERNAME/etiq_pick3 dataset [citation:11], which contains 62 episodes of teleoperated demonstrations. The observation includes a top camera view with bounding-box annotations highlighting the target tube.
Training Procedure
- Framework: LeRobot
- Policy type: ACT
- Chunk size: 20
- Action steps: 10
- Batch size: 8
- Training steps: 100,000 (final checkpoint at step 15K was performing well)
- VAE enabled: Yes
Evaluation
Add your evaluation results here.
How to Use
from lerobot.policies.act import ACTPolicy
policy = ACTPolicy.from_pretrained("YOUR_CORRECT_USERNAME/act_etiq_pick3_v1")
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