From 58b18410eeaa3347db047e35ca574a81d02b2ac7 Mon Sep 17 00:00:00 2001 From: Nikodem Bartnik Date: Thu, 14 May 2026 09:26:27 +0200 Subject: [PATCH] fix mistakes --- docs/source/cheat-sheet.mdx | 50 ++++++++++++++++++------------------- 1 file changed, 25 insertions(+), 25 deletions(-) diff --git a/docs/source/cheat-sheet.mdx b/docs/source/cheat-sheet.mdx index acae5e27b..088b3c587 100644 --- a/docs/source/cheat-sheet.mdx +++ b/docs/source/cheat-sheet.mdx @@ -76,44 +76,44 @@ lerobot-record \ While collecting the dataset you can control the process with your keyboard: Control the data recording flow using keyboard shortcuts: -- Press **Right Arrow (```→```)**: Early stop the current episode or reset time and move to the next. -- Press **Left Arrow (```←```)**: Cancel the current episode and re-record it. -- Press **Escape (```ESC```)**: Immediately stop the session, encode videos, and upload the dataset. +- Press **Right Arrow (```→```)**: Save episode and move to the next. +- Press **Left Arrow (```←```)**: Delete current episode and retry. +- Press **Escape (```ESC```)**: Stop, encode videos, and upload. ### Training Depending on your hardware training the policy might take a few hours. ``` lerobot-train \ - --dataset.repo_id=${HF_USER}/so101_dataset_test \ - --policy.type=act \ - --output_dir=outputs/train/act_so101_test \ - --job_name=act_so101_test \ - --policy.device=cuda \ - --wandb.enable=true \ - --policy.repo_id=${HF_USER}/policy_test \ - --steps=20000 - ``` + --dataset.repo_id=${HF_USER}/so101_dataset_test \ + --policy.type=act \ + --output_dir=outputs/train/act_so101_test \ + --job_name=act_so101_test \ + --policy.device=cuda \ + --wandb.enable=true \ + --policy.repo_id=${HF_USER}/policy_test \ + --steps=20000 +``` + +- Policy Types: ```act```, ```diffusion```, ```smolvla```, ```pi05``` +- Devices: ```cuda``` (NVIDIA), ```mps``` (Apple Silicon), ```cpu``` + - What you can change: - - polic.type: act, smolvla, pi05 - - policy.device: cuda, mps, cpu - - number of steps: how long will the model train ### Inference -Inference means running the trained policy/model on a robot. For that we use ```lerobot-rollout```. You will need to provide a path to your policy. It can be a local path or a path to Hugging Face for example "lerobot/folding_latest". Your cameras configuration need to match what was used when collecting the dataset. Duration is in seconds if unspecified it will run forever. +Inference means running the trained policy/model on a robot. For that we use ```lerobot-rollout```. You will need to provide a path to your policy. It can be a local path or a path to Hugging Face for example "lerobot/folding_latest". Your cameras configuration needs to match what was used when collecting the dataset. Duration is in seconds if unspecified, it will run forever. > [!TIP] -> If you are using the previous release V0.5.1 instead of ```lerobot-rollout``` you need to use ```lerobot-record``` +> If you are using the previous release V0.5.1 instead of ```lerobot-rollout``` you need to use ```lerobot-record```. More information [here](https://huggingface.co/docs/lerobot/v0.5.1/en/il_robots#run-inference-and-evaluate-your-policy). ``` bash lerobot-rollout \ - --strategy.type=base \ - --policy.path=${HF_USER}/my_policy \ - --robot.type=so101_follower \ - --robot.port=/dev/ttyACM1 \ - --robot.cameras="{ up: {type: opencv, index_or_path: /dev/video1, width: 640, height: 480, fps: 30}, side: {type: opencv, index_or_path: /dev/video5, width: 640, height: 480, fps: 30}}" \ - --task="Put lego brick into the transparent box" \ - --duration=60 + --strategy.type=base \ + --policy.path=${HF_USER}/my_policy \ + --robot.type=so101_follower \ + --robot.port=/dev/ttyACM1 \ + --robot.cameras="{ up: {type: opencv, index_or_path: /dev/video1, width: 640, height: 480, fps: 30}, side: {type: opencv, index_or_path: /dev/video5, width: 640, height: 480, fps: 30}}" \ + --task="Put lego brick into the transparent box" \ + --duration=60 ```