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README.md

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+---
+tags:
+- FrozenLake-v1-8x8-no_slippery
+- q-learning
+- reinforcement-learning
+- custom-implementation
+model-index:
+- name: q-FrozenLake-v1-8x8-noSlippery
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: FrozenLake-v1-8x8-no_slippery
+      type: FrozenLake-v1-8x8-no_slippery
+    metrics:
+    - type: mean_reward
+      value: 1.00 +/- 0.00
+      name: mean_reward
+      verified: false
+---
+
+# **Q-Learning** Agent playing **FrozenLake-v1**  
+This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .  
+
+## Usage  
+```python
+
+model = load_from_hub(repo_id="markeidsaune/q-FrozenLake-v1-8x8-noSlippery", 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"])
+
+evaluate_agent(env, model["max_steps"], model["n_eval_episodes"], model["qtable"], model["eval_seed"])
+
+```
+    

q-learning.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:73e33a53c72bed30b5b43d378f1031e1855998b11cb053d654674a1ccc32451b
+size 2452

results.json

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+{"env_id": "FrozenLake-v1", "mean_reward": 1.0, "n_eval_episodes": 100, "eval_datetime": "2023-03-29T15:19:58.923731"}