Update README.md

README.md

@@ -3,22 +3,24 @@ pipeline_tag: robotics
 tags:
 - lerobot
 library_name: lerobot
+datasets:
+- lerobot/svla_so101_pickplace
 ---
 
-SmolVLA: A vision-language-action model for affordable and efficient robotics
+## SmolVLA: A vision-language-action model for affordable and efficient robotics
 
 Resources and technical documentation:
 
-[Train using Google Colab Notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/lerobot/training-smolvla.ipynb#scrollTo=ZO52lcQtxseE)
-
-[SmolVLA HF Documentation](https://huggingface.co/docs/lerobot/smolvla)
-
 [SmolVLA Paper](https://huggingface.co/papers/2506.01844)
 
 [SmolVLA Blogpost](https://huggingface.co/blog/smolvla)
 
 [Code](https://github.com/huggingface/lerobot/blob/main/lerobot/common/policies/smolvla/modeling_smolvla.py)
 
+[Train using Google Colab Notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/lerobot/training-smolvla.ipynb#scrollTo=ZO52lcQtxseE)
+
+[SmolVLA HF Documentation](https://huggingface.co/docs/lerobot/smolvla)
+
 Designed by Hugging Face.
 
 This model has 450M parameters in total.
@@ -32,20 +34,27 @@ pip install -e ".[smolvla]"
 Example of finetuning the smolvla pretrained model (`smolvla_base`):
 ```bash
 python lerobot/scripts/train.py \
---policy.path=lerobot/smolvla_base \
---dataset.repo_id=danaaubakirova/svla_so100_task1_v3 \
---batch_size=64 \
---steps=200000
+  --policy.path=lerobot/smolvla_base \
+  --dataset.repo_id=lerobot/svla_so101_pickplace \
+  --batch_size=64 \
+  --steps=20000 \
+  --output_dir=outputs/train/my_smolvla \
+  --job_name=my_smolvla_training \
+  --policy.device=cuda \
+  --wandb.enable=true
 ```
 
 Example of finetuning the smolvla neural network with pretrained VLM and action expert
 intialized from scratch:
 ```bash
 python lerobot/scripts/train.py \
---policy.type=smolvla \
---dataset.repo_id=danaaubakirova/svla_so100_task1_v3 \
---batch_size=64 \
---steps=200000
+  --dataset.repo_id=lerobot/svla_so101_pickplace \
+  --batch_size=64 \
+  --steps=200000 \
+  --output_dir=outputs/train/my_smolvla \
+  --job_name=my_smolvla_training \
+  --policy.device=cuda \
+  --wandb.enable=true
 ```
 
 Example of using the smolvla pretrained model outside LeRobot training framework: