Update README.md

README.md

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----
-library_name: ml-agents
-tags:
-- Pyramids
-- deep-reinforcement-learning
-- reinforcement-learning
-- ML-Agents-Pyramids
----
-
-  # **ppo** Agent playing **Pyramids**
-  This is a trained model of a **ppo** agent playing **Pyramids**
-  using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
-
-  ## Usage (with ML-Agents)
-  The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
-
-  We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
-  - A *short tutorial* where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your
-  browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction
-  - A *longer tutorial* to understand how works ML-Agents:
-  https://huggingface.co/learn/deep-rl-course/unit5/introduction
-
-  ### Resume the training
-  ```bash
-  mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume
-  ```
-
-  ### Watch your Agent play
-  You can watch your agent **playing directly in your browser**
-
-  1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity
-  2. Step 1: Find your model_id: tungdao1998/ppo-Pyramids
-  3. Step 2: Select your *.nn /*.onnx file
-  4. Click on Watch the agent play 👀
-  
+
+ppo Agent playing Pyramids
+
+This is a trained model of a ppo agent playing Pyramids using the Unity ML-Agents Library.
+
+
+Usage (with ML-Agents)
+
+The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
+
+We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
+
+A short tutorial where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction
+A longer tutorial to understand how works ML-Agents: https://huggingface.co/learn/deep-rl-course/unit5/introduction
+
+Resume the training
+
+mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume
+
+
+Watch your Agent play
+
+You can watch your agent playing directly in your browser
+
+If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity
+Step 1: Find your model_id: tungdao1998/ppo-ML-Agents-Pyramids
+Step 2: Select your .nn /.onnx file
+Click on Watch the agent play 👀