Instructions to use lvtpsjlfj94/ACT_sim_handle_basket_ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use lvtpsjlfj94/ACT_sim_handle_basket_ft 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 β RoboSynChallenge handle_basket (fine-tuned)
LeRobot 0.3.3 ACT policy for the RoboSynChallenge simulation task handle_basket (CobotMagic dual-arm robot,
three 480x640 RGB cameras, 14-D joint state/action).
- Initialised from RoboSynChallenge/ACT_sim_mixer_operating weights (normalisation statistics recomputed from the task dataset).
- Fine-tuned for 14,000 steps on RoboSynChallenge/cobotmagic_Sim_handle_basket (1000 episodes), batch size 16, lr 1e-5, AMP; default ACT architecture (ResNet-18, dim 512, 4 enc / 1 dec layers, VAE, chunk size 50).
- Local check (
randomsetting, seeds 0 and 1, 10 episodes each): 11/20 successes, vs. 5/20 for the releasedRoboSynChallenge/ACT_sim_handle_basketunder the same protocol.
Evaluate with the RoboSynChallenge ACT adapter (LeRobot 0.3.3 required):
bash policy/act/eval.sh handle_basket random <path-to-this-checkpoint> 0 --headless True
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