Instructions to use jatinror/cartpole-ppo-agent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use jatinror/cartpole-ppo-agent with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="jatinror/cartpole-ppo-agent", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
CartPole PPO Agent
This repository contains a trained PPO (Proximal Policy Optimization) agent for the CartPole-v1 environment from OpenAI Gym.
The agent is trained to balance the pole on the cart as long as possible while maximizing the reward.
Features
- Environment: OpenAI Gym
CartPole-v1 - Algorithm: Proximal Policy Optimization (PPO)
- Trained Model:
ppo_cartpole.zip - Python 3.10+ compatible
- Direct Hugging Face Integration: Load model for evaluation or further training
Installation
- Clone the repository:
git clone https://huggingface.co/jatinror/cartpole-ppo-agent
cd cartpole-ppo-agent
-
- Downloads last month
- 7