YULI ZHU

> I tried to use the lerobot/aloha_sim_insertion_human dataset to train smolvla_base and simulate it in the aloha Gym simulation. However, the inference effect is poor. I'm not sure if this...

> I think you're right. I checked the pretraining dataset, and most of the robots are so100. I didn't even see aloha. So it may not be possible to use...

> I just tried train.py and eval.py in lerobot/scripts. For example, python lerobot/scripts/train.py --policy.path=lerobot/smolvla_base --dataset.repo_id=lerobot/aloha_sim_insertion_human --batch_size=64 --steps=20000. When running eval.py, select the aloha environment: --env.type=aloha have you erver tried shorter...

> ## What this does > This PR adds support for async inference. > > * async inference: decoupling of action prediction and execution, aimed at improving on adaptability to...

> Hey! We're working on merging it right now, you can find more details (and use it pre-merge, 😉) at [#1196](https://github.com/huggingface/lerobot/pull/1196) thx for ur soooo quick reply,I am really interested...

@StoneT2000 yes the success rate is still high(always over 99%) but I still dont know why it happened,it's always 100% in past time.In my view ,They are essentially the same...

> Whats the commands you are running? Are you using the dataset that we provided? my cmd is python -m mani_skill.trajectory.replay_trajectory --traj-path=/path_to_traj.h5 I've tried --use-env-states,but nothing improved.(Like PushCube 4/1000 is...

> Which dataset did you use? > > I need the full commands and the same files to reproduce. I download demonstrations from https://huggingface.co/datasets/haosulab/ManiSkill_Demonstrations/tree/main/demos For example,I try `python -m mani_skill.trajectory.replay_trajectory...