Remove unecessary id

This commit is contained in:
Simon Alibert
2025-05-12 19:01:30 +02:00
parent 06f0c579b7
commit 5a2f9b6589

View File

@@ -90,8 +90,7 @@ Connect the usb cable from your computer and the 5V power supply to the leader a
```bash
python -m lerobot.setup_motors \
--device.type=so100_leader \
--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
--device.port=/dev/tty.usbmodem575E0031751 # <- paste here the port found at previous step
```
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(
port="/dev/tty.usbmodem575E0031751",
id="my_awesome_leader_arm",
)
leader = KochLeader(config)
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:
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`).
## K. More Information