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chore: remove usernames + use entrypoints in docs, comments & sample commands (#2988)

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This commit is contained in:
Steven Palma
2026-02-18 22:46:12 +01:00
committed by GitHub
parent bc38261321
commit 5f15232271
17 changed files with 97 additions and 97 deletions
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docs/source/sarm.mdx
+4 -4
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@@ -269,7 +269,7 @@ This generates visualizations showing video frames with subtask boundaries overl
Train with **no annotations** - uses linear progress from 0 to 1:
```bash
python src/lerobot/scripts/lerobot_train.py \
lerobot-train \
--dataset.repo_id=your-username/your-dataset \
--policy.type=sarm \
--policy.annotation_mode=single_stage \
@@ -288,7 +288,7 @@ python src/lerobot/scripts/lerobot_train.py \
Train with **dense annotations only** (sparse auto-generated):
```bash
python src/lerobot/scripts/lerobot_train.py \
lerobot-train \
--dataset.repo_id=your-username/your-dataset \
--policy.type=sarm \
--policy.annotation_mode=dense_only \
@@ -307,7 +307,7 @@ python src/lerobot/scripts/lerobot_train.py \
Train with **both sparse and dense annotations**:
```bash
python src/lerobot/scripts/lerobot_train.py \
lerobot-train \
--dataset.repo_id=your-username/your-dataset \
--policy.type=sarm \
--policy.annotation_mode=dual \
@@ -468,7 +468,7 @@ This script:
Once you have the progress file, train your policy with RA-BC weighting. The progress file is auto-detected from the dataset path (`sarm_progress.parquet`). Currently PI0, PI0.5 and SmolVLA are supported with RA-BC:
```bash
python src/lerobot/scripts/lerobot_train.py \
lerobot-train \
--dataset.repo_id=your-username/your-dataset \
--policy.type=pi0 \
--use_rabc=true \