ONNX Model Zoo

underspirit/learn-rl

By underspirit · ↓ 1 · ♥ 0 · Updated 2025-11-16

What's in this repo

This page lists the files in underspirit/learn-rl, including Huggy-199992.onnx.

  • 1 ONNX models (.onnx files)
  • 20 files, including 4 .json, 3 .pth, 2 .pt, 1 .onnx, 1 .0, 1 .md
  • Last updated 2025-11-16

ONNX files

File Size Download
Huggy/Huggy-199992.onnx — Download

How to use

These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.

README

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: 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: underspirit/learn-rl
  3. Step 2: Select your .nn /.onnx file
  4. Click on Watch the agent play 👀

Model info

ml-agents tensorboard onnx Huggy deep-reinforcement-learning reinforcement-learning ML-Agents-Huggy region:us
↓ 1 ♥ 0

Created: 2025-11-15

Updated: 2025-11-16

View on Hugging Face

Files (20)

.gitattributes
Huggy/Huggy-199992.onnx ONNX
Huggy/Huggy-199992.pt
Huggy/checkpoint.pt
Huggy/events.out.tfevents.1763310355.1e5076c78a99.8506.0
README.md
config.json
configuration.yaml
ppo-LunarLander-v2.zip
ppo-LunarLander-v2/_stable_baselines3_version
ppo-LunarLander-v2/data
ppo-LunarLander-v2/policy.optimizer.pth
ppo-LunarLander-v2/policy.pth
ppo-LunarLander-v2/pytorch_variables.pth
ppo-LunarLander-v2/system_info.txt
replay.mp4
results.json
run_logs/Player-0.log
run_logs/timers.json
run_logs/training_status.json

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