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README.md

@@ -21,7 +21,7 @@ model-index:
       type: BreakoutNoFrameskip-v4
     metrics:
     - type: mean_reward
-      value: 2.4 +/- 3.04
+      value: 6.6 +/- 3.58
       name: mean_reward
 ---
 
@@ -149,7 +149,7 @@ pip3 install LightZero
     repo_id="OpenDILabCommunity/PongNoFrameskip-v4-MuZero",
     platform_info="[LightZero](https://github.com/opendilab/LightZero) and [DI-engine](https://github.com/opendilab/di-engine)",
     model_description="**LightZero** is an efficient, easy-to-understand open-source toolkit that merges Monte Carlo Tree Search (MCTS) with Deep Reinforcement Learning (RL), simplifying their integration for developers and researchers. More details are in paper [LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios](https://huggingface.co/papers/2310.08348).",
-    create_repo=True
+    create_repo=False
 )
 
 ```
@@ -290,7 +290,7 @@ exp_config = {
 - **Demo:** [video](https://huggingface.co/OpenDILabCommunity/BreakoutNoFrameskip-v4-MuZero/blob/main/replay.mp4)
 <!-- Provide the size information for the model. -->
 - **Parameters total size:** 24008.38 KB
-- **Last Update Date:** 2023-12-16
+- **Last Update Date:** 2023-12-20
 
 ## Environments
 <!-- Address questions around what environment the model is intended to be trained and deployed at, including the necessary information needed to be provided for future users. -->