Create README.md

README.md

@@ -1,3 +1,40 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+datasets:
+- JayLee131/vqbet_pusht
+pipeline_tag: robotics
+---
+# Model Card for ACT/AlohaTransferCube
+
+VQ-BeT (as per [Behavior Generation with Latent Actions](https://arxiv.org/abs/2403.03181)) trained for the `PushT` environment from [gym-pusht](https://github.com/huggingface/gym-pusht).
+
+![demo](demo.gif)
+
+## How to Get Started with the Model
+
+See the [LeRobot library](https://github.com/huggingface/lerobot) (particularly the [evaluation script](https://github.com/huggingface/lerobot/blob/main/lerobot/scripts/eval.py)) for instructions on how to load and evaluate this model.
+
+## Training Details
+
+The model was trained using this command:
+
+```bash
+python lerobot/scripts/train.py \
+  policy=vqbet \
+  env=pusht dataset_repo_id=lerobot/pusht \
+  wandb.enable=true \
+  device=cuda
+```
+
+
+## Evaluation
+
+The model was evaluated on the `PushT` environment from [gym-pusht](https://github.com/huggingface/gym-pusht). There are two evaluation metrics on a per-episode basis:
+
+- Maximum overlap with target (seen as `eval/avg_max_reward` in the charts above). This ranges in [0, 1].
+- Success: whether or not the maximum overlap is at least 95%.
+
+<blank>|Ours
+-|-
+Average max. overlap ratio | 0.887
+Success rate for 500 episodes (%) | 66.0