Upload DQN LunarLander-v2 trained agent

DQN-LunarLander-v2.zip

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DQN-LunarLander-v2/_stable_baselines3_version

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+1.7.0

DQN-LunarLander-v2/data

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+        "__abstractmethods__": "frozenset()",
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+        "high": "[inf inf inf inf inf inf inf inf]",
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+        "bounded_above": "[False False False False False False False False]",
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+    "batch_norm_stats_target": []
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DQN-LunarLander-v2/policy.optimizer.pth

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+size 557999

DQN-LunarLander-v2/policy.pth

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DQN-LunarLander-v2/pytorch_variables.pth

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+size 431

DQN-LunarLander-v2/system_info.txt

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+- OS: Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
+- Python: 3.8.10
+- Stable-Baselines3: 1.7.0
+- PyTorch: 1.13.1+cu116
+- GPU Enabled: True
+- Numpy: 1.21.6
+- Gym: 0.21.0

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: DQN
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+    metrics:
+    - type: mean_reward
+      value: 275.34 +/- 18.88
+      name: mean_reward
+      verified: false
+---
+
+# **DQN** Agent playing **LunarLander-v2**
+This is a trained model of a **DQN** agent playing **LunarLander-v2**
+using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
+
+## Usage (with Stable-baselines3)
+TODO: Add your code
+
+
+```python
+from stable_baselines3 import ...
+from huggingface_sb3 import load_from_hub
+
+...
+```

config.json

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results.json

@@ -0,0 +1 @@
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