readme: ---
  tags:
  - CartPole-v1
  - reinforce
  - reinforcement-learning
  - custom-implementation
  - deep-rl-class
  model-index:
  - name: Reinforce-CartPole-v1
    results:
    - task:
        type: reinforcement-learning
        name: reinforcement-learning
      dataset:
        name: CartPole-v1
        type: CartPole-v1
      metrics:
      - type: mean_reward
        value: 109.92 +/- 16.87
        name: mean_reward
        verified: false
  ---
  # **Q-Learning** Agent playing **CartPole-v1**
  
  This is a trained model of a **Reinforce** agent playing **CartPole-v1** .
  
  ## Usage
  
  ```python
  
  model = load_from_hub(repo_id="sayby/Reinforce-CartPole-v1", filename="model.pt")
  
  # 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["eval_seed"])
  
   
  ```
        