Add README

README.md

@@ -1,29 +1,36 @@
 # SAC Ant Agent
 
-A PPO agent trained on the MuJoCo Ant-v4 environment.
+A SAC agent trained on the MuJoCo Ant-v4 environment.
 
 ## Training Details
 - Algorithm: SAC
-- Timesteps: 2e6
-- Reward: ...
+- 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
 
-```bash
-pip install huggingface_hub huggingface_sb3
-
+```python
+!pip install huggingface_sb3
 # login to huggingFace
-huggingface-cli login
-```
-
+!huggingface-cli login
 
-```python
 from stable_baselines3 import SAC
-from huggingface_hub import hf_hub_download
+from huggingface_sb3 import load_from_hub
 
-model_file = hf_hub_download(
-    repo_id="your-username/ppo-ant-demo",
-    filename="model.zip"
+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_file)
+
+model = SAC.load(model_path)
+print(model.actor)
+print(model.critic)
 ```