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Remove unecessary id

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This commit is contained in:
Simon Alibert
2025-05-12 19:01:30 +02:00
parent 06f0c579b7
commit 5a2f9b6589
1 changed files with 2 additions and 4 deletions
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6
lerobot/common/robots/koch_follower/README.md
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@@ -90,8 +90,7 @@ Connect the usb cable from your computer and the 5V power supply to the leader a
```bash ```bash
python -m lerobot.setup_motors \ python -m lerobot.setup_motors \
--device.type=so100_leader \ --device.type=so100_leader \
--device.port=/dev/tty.usbmodem575E0031751 \ # <- paste here the port found at previous step --device.port=/dev/tty.usbmodem575E0031751 # <- paste here the port found at previous step
--device.id=my_awesome_leader_arm # <- give it a nice, unique name
``` ```
Note that the command above is equivalent to running the following script: Note that the command above is equivalent to running the following script:
@@ -103,7 +102,6 @@ Note that the command above is equivalent to running the following script:
config = KochLeaderConfig( config = KochLeaderConfig(
port="/dev/tty.usbmodem575E0031751", port="/dev/tty.usbmodem575E0031751",
id="my_awesome_leader_arm",
) )
leader = KochLeader(config) leader = KochLeader(config)
leader.setup_motors() leader.setup_motors()
@@ -319,7 +317,7 @@ python lerobot/scripts/control_robot.py \
``` ```
As you can see, it's almost the same command as previously used to record your training dataset. Two things changed: As you can see, it's almost the same command as previously used to record your training dataset. Two things changed:
1. There is an additional `--control.policy.path` argument which indicates the path to your policy checkpoint with (e.g. `outputs/train/eval_act_so100_test/checkpoints/last/pretrained_model`). You can also use the model repository if you uploaded a model checkpoint to the hub (e.g. `${HF_USER}/act_so100_test`). 1. There is an additional `--control.policy.path` argument which indicates the path to your policy checkpoint with (e.g. `outputs/train/eval_act_so100_test/checkpoints/last/pretrained_model`). You can also use the model repository if you uploaded a model checkpoint to the hub (e.g. `${HF_USER}/act_so100_test`).
2. The name of dataset begins by `eval` to reflect that you are running inference (e.g. `${HF_USER}/eval_act_so100_test`). 2. The name of dataset begins by `eval` to reflect that you are running inference (e.g. `${HF_USER}/eval_act_so100_test`).
## K. More Information ## K. More Information