---
tags:
- CartPole-v1
- reinforce
- reinforcement-learning
- custom-implementation
- deep-rl-class
model-index:
- name: DeepRL
  results:
  - task:
      type: reinforcement-learning
      name: reinforcement-learning
    dataset:
      name: CartPole-v1
      type: CartPole-v1
    metrics:
    - type: mean_reward
      value: 500.00 +/- 0.00
      name: mean_reward
      verified: false
---
    
  # **ppo** Agent playing **PushBlock**
  This is a trained model of a **ppo** agent playing **PushBlock** 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-PushBlock
  2. Step 1: Write your model_id: jackoyoungblood/DeepRL
  3. Step 2: Select your *.nn /*.onnx file
  4. Click on Watch the agent play 👀