
  # **ppo** Agent playing **Huggy**
  This is a trained model of a **ppo** agent playing **Huggy** 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
  ```
  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: coldra1n/Huggy
  3. Step 2: Select your *.nn /*.onnx file
  4. Click on Watch the agent play 👀 
  
{"library_name": "ml-agents", "tags": ["Huggy", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-Huggy"]}
ml-agents tensorboard onnx Huggy deep-reinforcement-learning reinforcement-learning ML-Agents-Huggy region:us
TAGS
#ml-agents #tensorboard #onnx #Huggy #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Huggy #region-us 


  # ppo Agent playing Huggy
  This is a trained model of a ppo agent playing Huggy using the Unity ML-Agents Library.
  
  ## Usage (with ML-Agents)
  The Documentation: URL
  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: URL
  - A *longer tutorial* to understand how works ML-Agents: URL

  ### Resume the training
  

  ### 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 URL
  2. Step 1: Find your model_id: coldra1n/Huggy
  3. Step 2: Select your *.nn /*.onnx file
  4. Click on Watch the agent play  
  
# ppo Agent playing Huggy
  This is a trained model of a ppo agent playing Huggy using the Unity ML-Agents Library.
  
  ## Usage (with ML-Agents)
  The Documentation: URL
  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: URL
  - A *longer tutorial* to understand how works ML-Agents: URL

  ### Resume the training
  

  ### 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 URL
  2. Step 1: Find your model_id: coldra1n/Huggy
  3. Step 2: Select your *.nn /*.onnx file
  4. Click on Watch the agent play
TAGS
#ml-agents #tensorboard #onnx #Huggy #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Huggy #region-us 
 # ppo Agent playing Huggy
  This is a trained model of a ppo agent playing Huggy using the Unity ML-Agents Library.
  
  ## Usage (with ML-Agents)
  The Documentation: URL
  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: URL
  - A *longer tutorial* to understand how works ML-Agents: URL

  ### Resume the training
  

  ### 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 URL
  2. Step 1: Find your model_id: coldra1n/Huggy
  3. Step 2: Select your *.nn /*.onnx file
  4. Click on Watch the agent play
TAGS
#ml-agents #tensorboard #onnx #Huggy #deep-reinforcement-learning #reinforcement-learning #ML-Agents-Huggy #region-us 
# ppo Agent playing Huggy
  This is a trained model of a ppo agent playing Huggy using the Unity ML-Agents Library.
  
  ## Usage (with ML-Agents)
  The Documentation: URL
  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: URL
  - A *longer tutorial* to understand how works ML-Agents: URL

  ### Resume the training
  

  ### 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 URL
  2. Step 1: Find your model_id: coldra1n/Huggy
  3. Step 2: Select your *.nn /*.onnx file
  4. Click on Watch the agent play