hangX/lerobot
1
0
Fork 0
forked from tangger/lerobot
Code Pull Requests Activity

chore(docs): prioritize use of entry points in docs + fix nightly badge (#1692)

Browse Source 
* chore(docs): fix typo in nightly badge

* chore(docs): prioritize the use of entrypoints for consistency
This commit is contained in:
Steven Palma
2025-08-07 14:25:44 +02:00
committed by GitHub
parent c66cd40176
commit ce3b9f627e
31 changed files with 105 additions and 107 deletions
Download Patch File Download Diff File Expand all files Collapse all files

16
docs/source/il_robots.mdx
View File

@@ -45,7 +45,7 @@ Note that the `id` associated with a robot is used to store the calibration file
<hfoptions id="teleoperate_so101">
<hfoption id="Command">
```bash
python -m lerobot.teleoperate \
lerobot-teleoperate \
--robot.type=so101_follower \
--robot.port=/dev/tty.usbmodem58760431541 \
--robot.id=my_awesome_follower_arm \
@@ -101,7 +101,7 @@ With `rerun`, you can teleoperate again while simultaneously visualizing the cam
<hfoptions id="teleoperate_koch_camera">
<hfoption id="Command">
```bash
python -m lerobot.teleoperate \
lerobot-teleoperate \
--robot.type=koch_follower \
--robot.port=/dev/tty.usbmodem58760431541 \
--robot.id=my_awesome_follower_arm \
@@ -174,7 +174,7 @@ Now you can record a dataset. To record 5 episodes and upload your dataset to th
<hfoptions id="record">
<hfoption id="Command">
```bash
python -m lerobot.record \
lerobot-record \
--robot.type=so101_follower \
--robot.port=/dev/tty.usbmodem585A0076841 \
--robot.id=my_awesome_follower_arm \
@@ -376,7 +376,7 @@ You can replay the first episode on your robot with either the command below or
<hfoptions id="replay">
<hfoption id="Command">
```bash
python -m lerobot.replay \
lerobot-replay \
--robot.type=so101_follower \
--robot.port=/dev/tty.usbmodem58760431541 \
--robot.id=my_awesome_follower_arm \
@@ -428,10 +428,10 @@ Your robot should replicate movements similar to those you recorded. For example
## Train a policy
To train a policy to control your robot, use the [`python -m lerobot.scripts.train`](https://github.com/huggingface/lerobot/blob/main/src/lerobot/scripts/train.py) script. A few arguments are required. Here is an example command:
To train a policy to control your robot, use the [`lerobot-train`](https://github.com/huggingface/lerobot/blob/main/src/lerobot/scripts/train.py) script. A few arguments are required. Here is an example command:
```bash
python -m lerobot.scripts.train \
lerobot-train \
--dataset.repo_id=${HF_USER}/so101_test \
--policy.type=act \
--output_dir=outputs/train/act_so101_test \
@@ -453,7 +453,7 @@ Training should take several hours. You will find checkpoints in `outputs/train/
To resume training from a checkpoint, below is an example command to resume from `last` checkpoint of the `act_so101_test` policy:
```bash
python -m lerobot.scripts.train \
lerobot-train \
--config_path=outputs/train/act_so101_test/checkpoints/last/pretrained_model/train_config.json \
--resume=true
```
@@ -490,7 +490,7 @@ You can use the `record` script from [`lerobot/record.py`](https://github.com/hu
<hfoptions id="eval">
<hfoption id="Command">
```bash
python -m lerobot.record \
lerobot-record \
--robot.type=so100_follower \
--robot.port=/dev/ttyACM1 \
--robot.cameras="{ up: {type: opencv, index_or_path: /dev/video10, width: 640, height: 480, fps: 30}, side: {type: intelrealsense, serial_number_or_name: 233522074606, width: 640, height: 480, fps: 30}}" \