    
  # **poca** Agent playing **SoccerTwos**
  This is a trained model of a **poca** agent playing **SoccerTwos** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
  
  ## Usage (with ML-Agents)
  The Documentation: https://github.com/huggingface/ml-agents#get-started
  We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:


  ### 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. Go to https://huggingface.co/spaces/unity/ML-Agents-SoccerTwos
  2. Step 1: Write your model_id: cfisicaro/poca-SoccerTwos
  3. Step 2: Select your *.nn /*.onnx file
  4. Click on Watch the agent play 👀
  
{"library_name": "ml-agents", "tags": ["unity-ml-agents", "ml-agents", "deep-reinforcement-learning", "reinforcement-learning", "ML-Agents-SoccerTwos"]}
ml-agents tensorboard onnx unity-ml-agents deep-reinforcement-learning reinforcement-learning ML-Agents-SoccerTwos region:us
TAGS
#ml-agents #tensorboard #onnx #unity-ml-agents #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SoccerTwos #region-us 

    
  # poca Agent playing SoccerTwos
  This is a trained model of a poca agent playing SoccerTwos 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:


  ### Resume the training
  
  ### Watch your Agent play
  You can watch your agent playing directly in your browser:.
  
  1. Go to URL
  2. Step 1: Write your model_id: cfisicaro/poca-SoccerTwos
  3. Step 2: Select your *.nn /*.onnx file
  4. Click on Watch the agent play 
  
# poca Agent playing SoccerTwos
  This is a trained model of a poca agent playing SoccerTwos 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:


  ### Resume the training
  
  ### Watch your Agent play
  You can watch your agent playing directly in your browser:.
  
  1. Go to URL
  2. Step 1: Write your model_id: cfisicaro/poca-SoccerTwos
  3. Step 2: Select your *.nn /*.onnx file
  4. Click on Watch the agent play
TAGS
#ml-agents #tensorboard #onnx #unity-ml-agents #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SoccerTwos #region-us 
 # poca Agent playing SoccerTwos
  This is a trained model of a poca agent playing SoccerTwos 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:


  ### Resume the training
  
  ### Watch your Agent play
  You can watch your agent playing directly in your browser:.
  
  1. Go to URL
  2. Step 1: Write your model_id: cfisicaro/poca-SoccerTwos
  3. Step 2: Select your *.nn /*.onnx file
  4. Click on Watch the agent play
TAGS
#ml-agents #tensorboard #onnx #unity-ml-agents #deep-reinforcement-learning #reinforcement-learning #ML-Agents-SoccerTwos #region-us 
# poca Agent playing SoccerTwos
  This is a trained model of a poca agent playing SoccerTwos 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:


  ### Resume the training
  
  ### Watch your Agent play
  You can watch your agent playing directly in your browser:.
  
  1. Go to URL
  2. Step 1: Write your model_id: cfisicaro/poca-SoccerTwos
  3. Step 2: Select your *.nn /*.onnx file
  4. Click on Watch the agent play