add more base models to generate model card

src/lerobot/policies/pretrained.py

@@ -248,7 +248,13 @@ class PreTrainedPolicy(nn.Module, HubMixin, abc.ABC):
     def generate_model_card(
         self, dataset_repo_id: str, model_type: str, license: str | None, tags: list[str] | None
     ) -> ModelCard:
-        base_model = "lerobot/smolvla_base" if model_type == "smolvla" else None  # Set a base model
+        base_model_mapping = {
+            "smolvla": "lerobot/smolvla_base",
+            "pi0": "lerobot/pi0_base",
+            "pi05": "lerobot/pi05_base",
+            "pi0_fast": "lerobot/pi0fast-base",
+            "xvla": "lerobot/xvla-base",
+        }
 
         card_data = ModelCardData(
             license=license or "apache-2.0",
@@ -257,7 +263,7 @@ class PreTrainedPolicy(nn.Module, HubMixin, abc.ABC):
             tags=list(set(tags or []).union({"robotics", "lerobot", model_type})),
             model_name=model_type,
             datasets=dataset_repo_id,
-            base_model=base_model,
+            base_model=base_model_mapping(model_type, None),
         )
 
         template_card = (

src/lerobot/templates/lerobot_modelcard_template.md

@@ -73,14 +73,17 @@ _Writes checkpoints to `outputs/train/<desired_policy_repo_id>/checkpoints/`._
 ### Evaluate the policy/run inference
 
 ```bash
-lerobot-record \
-  --robot.type=so100_follower \
-  --dataset.repo_id=<hf_user>/eval_<dataset> \
+lerobot-rollout \
+  --strategy.type=base \
+  --robot.type=so101_follower \
+  --robot.port=/dev/ttyACM0 \
+  --robot.cameras="{ up: {type: opencv, index_or_path: /dev/video1, width: 640, height: 480, fps: 30}, side: {type: opencv, index_or_path: /dev/video5, width: 640, height: 480, fps: 30}}" \
   --policy.path=<hf_user>/<desired_policy_repo_id> \
-  --episodes=10
+  --task="Put lego brick into the transparent box" \
+  --duration=60
 ```
 
-Prefix the dataset repo with **eval\_** and supply `--policy.path` pointing to a local or hub checkpoint.
+If you want to record a dataset while testing the policy use `--dataset.repo_id=<hf_user>/eval_dataset_name` it is important to use the prefix **eval\_**. For the policy path use the policy from the Hugging Face Hub or a local one. Skipping duration will make the policy run indefinitely.
 
 ---