Update README.md

README.md

@@ -40,39 +40,20 @@ Then install the following modules :
 
 
 ```sh
-pip install gym==0.26.2
-```
-
-Install also pyglet for the rendering.
-
-```sh
-pip install pyglet==2.0.10
+pip install gymnasium
 ```
 
 ```sh
-pip install numpy==1.26.4
+pip install "gymnasium[classic-control]"
 ```
 
-If needed 
-
-```sh
-pip install pygame==2.5.2
-```
-
-```sh
-pip install PyQt5
-```
-
-```sh
-pip install opencv-python
-```
 
 ### Usage
 
 Here is an example of how to use Gym to solve the `CartPole-v1` environment [Documentation](https://gymnasium.farama.org/environments/classic_control/cart_pole/):
 
 ```python
-import gym
+import gymnasium as gym
 
 # Create the environment
 env = gym.make("CartPole-v1", render_mode="human")
@@ -144,7 +125,7 @@ Stable-Baselines3 (SB3) is a high-level RL library that provides various algorit
 
 ```sh
 pip install stable-baselines3
-pip install stable-baselines3[extra]
+pip install "stable-baselines3[extra]"
 pip install moviepy
 ```
 
@@ -163,7 +144,7 @@ Hugging Face Hub is a platform for easy sharing and versioning of trained machin
 #### Installation of `huggingface_sb3`
 
 ```sh
-pip install huggingface-sb3==2.3.1
+pip install huggingface-sb3
 ```
 
 #### Upload the model on the Hub
@@ -185,7 +166,7 @@ Weights & Biases (W&B) is a tool for machine learning experiment management. Wit
 You'll need to install both `wand` and `tensorboar`.
 
 ```shell
-pip install wandb tensorboard
+pip install wandb 
 ```
 
 Use the documentation of [Stable-Baselines3](https://stable-baselines3.readthedocs.io/en/master/) and [Weights & Biases](https://docs.wandb.ai/guides/integrations/stable-baselines-3) to track the CartPole training. Make the run public.