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Upload README.md with huggingface_hub

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  1. README.md +3 -3
README.md CHANGED
@@ -21,7 +21,7 @@ model-index:
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  type: PongNoFrameskip-v4
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  metrics:
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  - type: mean_reward
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- value: 5.8 +/- 4.92
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  name: mean_reward
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  ---
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@@ -129,7 +129,7 @@ from huggingface_ding import push_model_to_hub
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  # Instantiate the agent
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  agent = EfficientZeroAgent(env_id="PongNoFrameskip-v4", exp_name="PongNoFrameskip-v4-EfficientZero")
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  # Train the agent
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- return_ = agent.train(step=int(500000))
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  # Push model to huggingface hub
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  push_model_to_hub(
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  agent=agent.best,
@@ -289,7 +289,7 @@ exp_config = {
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  - **Demo:** [video](https://huggingface.co/OpenDILabCommunity/PongNoFrameskip-v4-EfficientZero/blob/main/replay.mp4)
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  <!-- Provide the size information for the model. -->
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  - **Parameters total size:** 33023.14 KB
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- - **Last Update Date:** 2024-01-08
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  ## Environments
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  <!-- 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. -->
 
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  type: PongNoFrameskip-v4
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  metrics:
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  - type: mean_reward
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+ value: 20.4 +/- 0.66
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  name: mean_reward
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  ---
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  # Instantiate the agent
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  agent = EfficientZeroAgent(env_id="PongNoFrameskip-v4", exp_name="PongNoFrameskip-v4-EfficientZero")
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  # Train the agent
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+ return_ = agent.train(step=int(2000000))
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  # Push model to huggingface hub
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  push_model_to_hub(
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  agent=agent.best,
 
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  - **Demo:** [video](https://huggingface.co/OpenDILabCommunity/PongNoFrameskip-v4-EfficientZero/blob/main/replay.mp4)
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  <!-- Provide the size information for the model. -->
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  - **Parameters total size:** 33023.14 KB
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+ - **Last Update Date:** 2024-01-16
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  ## Environments
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  <!-- 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. -->