fix old docs and comments

docs/source/act.mdx

@@ -76,7 +76,7 @@ If your local computer doesn't have a powerful GPU, you can utilize Google Colab
 
 ## Evaluating ACT
 
-Once training is complete, you can evaluate your ACT policy using the `lerobot-record` command with your trained policy. This will run inference and record evaluation episodes:
+Once training is complete, you can evaluate your ACT policy using the `lerobot-rollout` command with your trained policy. This will run inference and record evaluation episodes:
 
 ```bash
 lerobot-rollout \

docs/source/earthrover_mini_plus.mdx

@@ -194,8 +194,8 @@ lerobot-record \
     --dataset.single_task="Navigate around obstacles" \
     --dataset.streaming_encoding=true \
     --dataset.encoder_threads=2 \
-    # --dataset.rgb_encoder.vcodec=auto \
     --display_data=true
+    # Optionally, set --dataset.rgb_encoder.vcodec=auto to pick a specific video codec
 ```
 
 Replace `your_username/dataset_name` with your Hugging Face username and a name for your dataset.

docs/source/hope_jr.mdx

@@ -232,8 +232,8 @@ lerobot-record \
     --dataset.private=true \
     --dataset.streaming_encoding=true \
     --dataset.encoder_threads=2 \
-    # --dataset.rgb_encoder.vcodec=auto \
     --display_data=true
+    # Optionally, set --dataset.rgb_encoder.vcodec=auto to pick a specific video codec
 ```
 
 ### Replay
@@ -278,6 +278,6 @@ lerobot-record \
   --dataset.num_episodes=10 \
   --dataset.streaming_encoding=true \
   --dataset.encoder_threads=2 \
-  # --dataset.rgb_encoder.vcodec=auto \
   --policy.path=outputs/train/hopejr_hand/checkpoints/last/pretrained_model
+  # Optionally, set --dataset.rgb_encoder.vcodec=auto to pick a specific video codec
 ```

docs/source/il_robots.mdx

@@ -207,8 +207,8 @@ lerobot-record \
     --dataset.num_episodes=5 \
     --dataset.single_task="Grab the black cube" \
     --dataset.streaming_encoding=true \
-    # --dataset.rgb_encoder.vcodec=auto \
     --dataset.encoder_threads=2
+    # Optionally, set --dataset.rgb_encoder.vcodec=auto to pick a specific video codec
 ```
 </hfoption>
 <hfoption id="API example">
@@ -418,7 +418,7 @@ If you want to dive deeper into this important topic, you can check out the [blo
 
 ## Visualize a dataset
 
-If you uploaded your dataset to the hub with `--control.push_to_hub=true`, you can [visualize your dataset online](https://huggingface.co/spaces/lerobot/visualize_dataset) by copy pasting your repo id given by:
+If you uploaded your dataset to the hub with `--dataset.push_to_hub=true`, you can [visualize your dataset online](https://huggingface.co/spaces/lerobot/visualize_dataset) by copy pasting your repo id given by:
 
 ```bash
 echo ${HF_USER}/so101_test

docs/source/lerobot-dataset-v3.mdx

@@ -44,8 +44,8 @@ lerobot-record \
   --dataset.num_episodes=5 \
   --dataset.single_task="Grab the black cube" \
   --dataset.streaming_encoding=true \
-  # --dataset.rgb_encoder.vcodec=auto \
   --dataset.encoder_threads=2
+  # Optionally, set --dataset.rgb_encoder.vcodec=auto to pick a specific video codec
 ```
 
 See the [recording guide](./il_robots#record-a-dataset) for more details.

docs/source/openarm.mdx

@@ -205,9 +205,10 @@ lerobot-record \
     --teleop.type=openarm_leader \
     --teleop.port=can1 \
     --teleop.id=my_leader \
-    --repo-id=my_hf_username/my_openarm_dataset \
-    --fps=30 \
-    --num-episodes=10
+    --dataset.repo_id=my_hf_username/my_openarm_dataset \
+    --dataset.single_task="Grab the black cube" \
+    --dataset.fps=30 \
+    --dataset.num_episodes=10
 ```
 
 ## Configuration Options

docs/source/reachy2.mdx

@@ -161,8 +161,8 @@ lerobot-record \
     --dataset.private=true \
     --dataset.streaming_encoding=true \
     --dataset.encoder_threads=2 \
-    # --dataset.rgb_encoder.vcodec=auto \
     --display_data=true
+    # Optionally, set --dataset.rgb_encoder.vcodec=auto to pick a specific video codec
 ```
 
 #### Specific Options
@@ -203,8 +203,8 @@ lerobot-record \
     --dataset.private=true \
     --dataset.streaming_encoding=true \
     --dataset.encoder_threads=2 \
-    # --dataset.rgb_encoder.vcodec=auto \
     --display_data=true
+    # Optionally, set --dataset.rgb_encoder.vcodec=auto to pick a specific video codec
 ```
 
 ##### `--robot.use_external_commands`

docs/source/smolvla.mdx

@@ -100,20 +100,19 @@ Once you are logged in, you can run inference in your setup by doing:
 lerobot-rollout \
   --strategy.type=base \
   --robot.type=so101_follower \
-  --robot.port=/dev/ttyACM0 \ # <- Use your port
-  --robot.id=my_blue_follower_arm \ # <- Use your robot id
-  --robot.cameras="{ front: {type: opencv, index_or_path: 8, width: 640, height: 480, fps: 30}}" \ # <- Use your cameras
-  --task="Grasp a lego block and put it in the bin." \ # <- Use the same task description you used in your dataset recording
-  # <- RTC optional, use when running on low power hardware \
-  # --inference.type=rtc \
-  # --inference.rtc.execution_horizon=10 \
-  # --inference.rtc.max_guidance_weight=10.0 \
-  # <- Teleop optional if you want to teleoperate in between episodes \
-  # --teleop.type=so100_leader \
-  # --teleop.port=/dev/ttyACM0 \
-  # --teleop.id=my_red_leader_arm \
-  # --display_data=true #optional use if you want to see the camera stream \
-  --policy.path=HF_USER/FINETUNE_MODEL_NAME # <- Use your fine-tuned model
+  --robot.port=/dev/ttyACM0 \
+  --robot.id=my_blue_follower_arm \
+  --robot.cameras="{ front: {type: opencv, index_or_path: 8, width: 640, height: 480, fps: 30}}" \
+  --task="Grasp a lego block and put it in the bin." \
+  --policy.path=HF_USER/FINETUNE_MODEL_NAME
 ```
 
+Replace `--robot.port`, `--robot.id`, `--robot.cameras`, `--task`, and `--policy.path` with your own port, robot ID, camera setup, task description (matching what you used when recording your dataset), and fine-tuned model repo ID.
+
+A few optional flags you can add to the command above:
+
+- **RTC** (useful on low-power hardware): `--inference.type=rtc --inference.rtc.execution_horizon=10 --inference.rtc.max_guidance_weight=10.0`
+- **Teleoperate in between episodes**: `--teleop.type=so100_leader --teleop.port=/dev/ttyACM0 --teleop.id=my_red_leader_arm`
+- **See the camera stream**: `--display_data=true`
+
 Depending on your evaluation setup, you can configure the duration and the number of episodes to record for your evaluation suite.