Test commit

Pixelcopter-PLE-v0.zip

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Pixelcopter-PLE-v0/_stable_baselines3_version

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+1.7.0

Pixelcopter-PLE-v0/data

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+}

Pixelcopter-PLE-v0/policy.optimizer.pth

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+size 41601

Pixelcopter-PLE-v0/policy.pth

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+size 42369

Pixelcopter-PLE-v0/pytorch_variables.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
+size 431

Pixelcopter-PLE-v0/system_info.txt

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+- OS: Linux-5.15.0-69-generic-x86_64-with-glibc2.31 # 76~20.04.1-Ubuntu SMP Mon Mar 20 15:54:19 UTC 2023
+- Python: 3.9.0
+- Stable-Baselines3: 1.7.0
+- PyTorch: 1.13.1+cu117
+- GPU Enabled: True
+- Numpy: 1.23.2
+- Gym: 0.24.0

README.md

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+---
+library_name: stable-baselines3
+tags:
+- Pixelcopter-PLE-v0
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: A2C
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: Pixelcopter-PLE-v0
+      type: Pixelcopter-PLE-v0
+    metrics:
+    - type: mean_reward
+      value: 57.00 +/- 0.00
+      name: mean_reward
+      verified: false
+---
+
+# **A2C** Agent playing **Pixelcopter-PLE-v0**
+This is a trained model of a **A2C** agent playing **Pixelcopter-PLE-v0**
+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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It allows to keep variance\n        above zero and prevent it from growing too fast. 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results.json

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