| # SAC Ant Agent | |
| A SAC agent trained on the MuJoCo Ant-v4 environment. | |
| ## Training Details | |
| - Algorithm: SAC | |
| - Timesteps: 2.4e6 | |
| ``` | |
| - learning_rate=3e-4, | |
| - buffer_size=1_000_000, # 经验回放缓冲区大小. 这个参数PPO没有 | |
| - batch_size=256, # 默认256 | |
| - tau=0.005, # 软更新系数 | |
| - gamma=0.99, # 折扣因子 | |
| - train_freq=1, # 每步都训练,采集多少个环境步的数据后训练一次 | |
| - gradient_steps=1, # 对replayBuffer中读取到的batch,进行多少次梯度下降更新 | |
| ``` | |
| ## Usage | |
| ```python | |
| !pip install huggingface_sb3 | |
| # login to huggingFace | |
| !huggingface-cli login | |
| from stable_baselines3 import SAC | |
| from huggingface_sb3 import load_from_hub | |
| model_path = load_from_hub( # This function only returns the path of the cached model | |
| repo_id="buffaX/sac-ant-v4", | |
| filename="sac_ant.zip" | |
| ) | |
| model = SAC.load(model_path) | |
| print(model.actor) | |
| print(model.critic) | |
| ``` | |