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Upload folder using huggingface_hub

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  1. README.md +35 -0
  2. q-learning.pkl +3 -0
  3. replay.mp4 +0 -0
  4. results.json +1 -0
README.md ADDED
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+ ---
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+ tags:
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+ - Taxi-v3
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+ - q-learning
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+ - reinforcement-learning
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+ - custom-implementation
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+ model-index:
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+ - name: Taxi-v3
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+ results:
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+ - task:
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+ type: reinforcement-learning
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+ name: reinforcement-learning
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+ dataset:
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+ name: Taxi-v3
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+ type: Taxi-v3
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+ metrics:
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+ - type: mean_reward
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+ value: 7.48 +/- 2.78
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+ name: mean_reward
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+ verified: false
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+ ---
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+
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+ # **Q-Learning** Agent playing1 **Taxi-v3**
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+ This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
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+
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+ ## Usage
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+
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+ ```python
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+
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+ model = load_from_hub(repo_id="Promiseve/Taxi-v3", filename="q-learning.pkl")
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+
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+ # Don't forget to check if you need to add additional attributes (is_slippery=False etc)
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+ env = gym.make(model["env_id"])
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+ ```
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+
q-learning.pkl ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:527d2a75743161451759d05877507fb0d294eaadfc2f5d549612317dc98792de
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+ size 24570
replay.mp4 ADDED
Binary file (120 kB). View file
 
results.json ADDED
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+ {"env_id": "Taxi-v3", "mean_reward": 7.48, "n_eval_episodes": 100, "eval_datetime": "2023-09-04T04:13:27.934948"}