From 5a6069daf468cbdc0bc93762cb691d4ee5c49546 Mon Sep 17 00:00:00 2001
From: Dominik Roth <dominik.roth.dev@gmail.com>
Date: Fri, 31 May 2024 18:25:42 +0200
Subject: [PATCH] Showcase TRPL in README

---
 README.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index 462b097..c6e2971 100644
--- a/README.md
+++ b/README.md
@@ -23,11 +23,11 @@ Fancy RL provides two main components:
 1. **Ready-to-use Classes for PPO / TRPL**: These classes allow you to quickly get started with reinforcement learning algorithms, enjoying the performance and hackability that comes with using TorchRL.
 
    ```python
-   from fancy_rl import PPO
+   from fancy_rl import PPO, TRPL
 
-   ppo = PPO("CartPole-v1")
+   model = TRPL("CartPole-v1")
 
-   ppo.train()
+   model.train()
    ```
 
    For environments, you can pass any [gymnasium](https://gymnasium.farama.org/) or [Fancy Gym](https://alrhub.github.io/fancy_gym/) environment ID as a string, a function returning a gymnasium environment, or an already instantiated gymnasium environment. Future plans include supporting other torchrl environments.