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README.md

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+---
+tags:
+- CartPole-v1
+- q-learning
+- reinforcement-learning
+- custom-implementation
+model-index:
+- name: q_learning-Cartpole
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: CartPole-v1
+      type: CartPole-v1
+    metrics:
+    - type: mean_reward
+      value: 248.33 +/- 140.57
+      name: mean_reward
+      verified: false
+---
+
+  # **Q-Learning** Agent playing1 **CartPole-v1**
+  This is a trained model of a **Q-Learning** agent playing **CartPole-v1** .
+
+  ## Usage
+
+  ```python
+
+  model = load_from_hub(repo_id="erfan1380/q_learning-Cartpole", filename="q-learning.pkl")
+
+  # Don't forget to check if you need to add additional attributes (is_slippery=False etc)
+  env = gym.make(model["env_id"])
+  ```
+  

q-learning.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:915d451cb0a1a045dca76ed55939ea97f94407f2f24efadbd30277c4480c4af0
+size 43560389

results.json

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+{"env_id": "CartPole-v1", "mean_reward": 248.332, "n_eval_episodes": 500, "eval_datetime": "2024-05-06T22:39:34.808501"}