Upload policy weights, train config and readme

README.md

@@ -6,8 +6,8 @@ model_name: act
 pipeline_tag: robotics
 tags:
 - lerobot
-- act
 - robotics
+- act
 ---
 
 # Model Card for act
@@ -31,7 +31,7 @@ Below is the short version on how to train and run inference/eval:
 ### Train from scratch
 
 ```bash
-python -m lerobot.scripts.train \
+lerobot-train \
   --dataset.repo_id=${HF_USER}/<dataset> \
   --policy.type=act \
   --output_dir=outputs/train/<desired_policy_repo_id> \
@@ -46,8 +46,8 @@ _Writes checkpoints to `outputs/train/<desired_policy_repo_id>/checkpoints/`._
 ### Evaluate the policy/run inference
 
 ```bash
-python -m lerobot.record \
-  --robot.type=so101_follower \
+lerobot-record \
+  --robot.type=so100_follower \
   --dataset.repo_id=<hf_user>/eval_<dataset> \
   --policy.path=<hf_user>/<desired_policy_repo_id> \
   --episodes=10

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:2d475be692bc1c22c1510cf5213e2a8f6f03c9865edd19e3facdac51b73e4746
+oid sha256:393c19251ae093358743e0ddc63513c35c52ca1623e9fdfcdb5e561a9d073a36
 size 206700800

train_config.json

@@ -161,7 +161,7 @@
         "project": "lerobot",
         "entity": null,
         "notes": null,
-        "run_id": "7ni4spjp",
+        "run_id": "m03hpc6r",
         "mode": null
     }
 }