Initial commit

README.md

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+---
+library_name: stable-baselines3
+tags:
+- CartPole-v1
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: A2C
+  results:
+  - metrics:
+    - type: mean_reward
+      value: 280.00 +/- 0.00
+      name: mean_reward
+    task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: CartPole-v1
+      type: CartPole-v1
+---
+
+# **A2C** Agent playing **CartPole-v1**
+This is a trained model of a **A2C** agent playing **CartPole-v1**
+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
+
+...
+```

a2c-CartPole-v1.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:0aba8b167d056b523a8cb6c64787ae20ec393d6f980a965b20b4e6cd7e0f9ec4
+size 342200698

a2c-CartPole-v1/_stable_baselines3_version

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+1.6.0

a2c-CartPole-v1/policy.optimizer.pth

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+size 227166841

a2c-CartPole-v1/policy.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:da89da7a121dbeea035c63fcbb148c2758d873254c8190b8b66fa3f2dd4d71f0
+size 113582785

a2c-CartPole-v1/pytorch_variables.pth

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

a2c-CartPole-v1/system_info.txt

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+OS: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
+Python: 3.7.13
+Stable-Baselines3: 1.6.0
+PyTorch: 1.12.0+cu113
+GPU Enabled: True
+Numpy: 1.19.5
+Gym: 0.21.0

results.json

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+{"mean_reward": 280.0, "std_reward": 0.0, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-08-07T02:07:54.859298"}