Instructions to use umjunsik1323/Agenlus_Models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use umjunsik1323/Agenlus_Models with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="umjunsik1323/Agenlus_Models", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Agenlus Model Hub π
Welcome to your Agenlus Reinforcement Learning repository! This repository hosts multiple trained models.
π Models Summary
| Model Name | Environment | Algorithm | Best Score | Episodes | Links |
|---|---|---|---|---|---|
| model_cartpole-v1_1780399885 | CartPole-v1 |
PyTorch |
246.56 | 100 | Browse Files |
π Model Details & Instructions
π¦ model_cartpole-v1_1780399885
- Environment:
CartPole-v1 - RL Algorithm:
PyTorch - Best Avg Reward:
246.56 - Episodes Trained:
100
Description: Locally trained PyTorch model stacked for system/CartPole-v1
How to load:
// Load using ONNX Runtime Web:
const session = await ort.InferenceSession.create('https://huggingface.co/umjunsik1323/Agenlus_Models/resolve/8a7591e3b133d34645fb4144d4c43fba38764014/model_cartpole-v1_1780399885/model.onnx');
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