Reupload with model files and replay

README.md

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+---
+library_name: stable-baselines3
+tags:
+- PongNoFrameskip-v4
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: DQN
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: PongNoFrameskip-v4
+      type: PongNoFrameskip-v4
+    metrics:
+    - type: mean_reward
+      value: -21.00 +/- 0.00
+      name: mean_reward
+      verified: false
+---
+
+# **DQN** Agent playing **PongNoFrameskip-v4**
+This is a trained model of a **DQN** agent playing **PongNoFrameskip-v4**
+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
+
+...
+```

pong-dqn.zip

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+size 13754324

pong-dqn/_stable_baselines3_version

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+2.6.0

pong-dqn/policy.optimizer.pth

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+size 1120

pong-dqn/policy.pth

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+size 13505178

pong-dqn/pytorch_variables.pth

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+size 864

pong-dqn/system_info.txt

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+- OS: Linux-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025
+- Python: 3.11.12
+- Stable-Baselines3: 2.6.0
+- PyTorch: 2.6.0+cu124
+- GPU Enabled: False
+- Numpy: 2.0.2
+- Cloudpickle: 3.1.1
+- Gymnasium: 1.1.1
+- OpenAI Gym: 0.25.2

results.json

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+{"mean_reward": -21.0, "std_reward": 0.0, "is_deterministic": false, "n_eval_episodes": 10, "eval_datetime": "2025-05-01T00:00:18.628583"}