second commit

README.md

@@ -20,33 +20,3 @@ model-index:
       name: mean_reward
       verified: false
 ---
-
-# **PPO** Agent playing **LunarLander-v2**
-This is a trained model of a **PPO** agent playing **LunarLander-v2**
-using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
-
-## Usage (with Stable-baselines3)
-First DL agent. Feel free to use for whatever lunar landings are required.
-
-
-```python
-# To load it and watch it land (on your computer NOT collab! You have to ditch render-mode="human" to run it in a notebook without visuals)
-import gym
-
-from huggingface_sb3 import load_from_hub
-from stable_baselines3 import PPO
-from stable_baselines3.common.evaluation import evaluate_policy
-
-# Retrieve the model from the hub
-## repo_id =  id of the model repository from the Hugging Face Hub (repo_id = {organization}/{repo_name})
-## filename = name of the model zip file from the repository
-checkpoint = load_from_hub(repo_id="MattStammers/ppo-LunarLander-v2", filename="ppo-LunarLander-v2.zip")
-model = PPO.load(checkpoint)
-
-# Evaluate the agent and watch it land!
-eval_env = gym.make('LunarLander-v2', render_mode="human")
-mean_reward, std_reward = evaluate_policy(model, eval_env, n_eval_episodes=10, deterministic=True)
-print(f"mean_reward={mean_reward:.2f} +/- {std_reward}")
-
-...
-```