readme: ---
  library_name: stable-baselines3
  tags:
  - PandaReachDense-v2
  - deep-reinforcement-learning
  - reinforcement-learning
  - stable-baselines3
  model-index:
  - name: A2C
    results:
    - task:
        type: reinforcement-learning
        name: reinforcement-learning
      dataset:
        name: PandaReachDense-v2
        type: PandaReachDense-v2
      metrics:
      - type: mean_reward
        value: -1.65 +/- 0.14
        name: mean_reward
        verified: false
  ---
  
  # **A2C** Agent playing **PandaReachDense-v2**
  This is a trained model of a **A2C** agent playing **PandaReachDense-v2**
  using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
  
  ## Usage (with Stable-baselines3)
  
  ```python
  import pybullet_envs
  import panda_gym
  import gym
  
  import os
  
  from huggingface_sb3 import load_from_hub, package_to_hub
  
  from stable_baselines3 import A2C
  from stable_baselines3.common.evaluation import evaluate_policy
  from stable_baselines3.common.vec_env import DummyVecEnv, VecNormalize
  from stable_baselines3.common.env_util import make_vec_env
  
  from huggingface_hub import notebook_login
  
  load_model = load_from_hub(
  	repo_id="kinkpunk/a2c-PandaReachDense-v2",
  	filename="a2c-PandaReachDense-v2.zip",
  )
  
  model = A2C.load(load_model)
  
  ```
  