ONNX Model Zoo

miguepez/poca-SoccerTwos

By miguepez · ↓ 0 · ♥ 0 · Updated 2025-07-01

What's in this repo

This page lists the files in miguepez/poca-SoccerTwos, including SoccerTwos.onnx, SoccerTwos-1499592.onnx, SoccerTwos-1999972.onnx and more.

  • 8 ONNX models (.onnx files)
  • 32 files, including 8 .onnx, 8 .pt, 8 .log, 3 .json, 2 .0, 1 .md
  • Last updated 2025-07-01

ONNX files

File Size Download
SoccerTwos.onnx — Download
SoccerTwos/SoccerTwos-1499592.onnx — Download
SoccerTwos/SoccerTwos-1999972.onnx — Download
SoccerTwos/SoccerTwos-2499380.onnx — Download
SoccerTwos/SoccerTwos-2499951.onnx — Download
SoccerTwos/SoccerTwos-2607934.onnx — Download
SoccerTwos/SoccerTwos-499918.onnx — Download
SoccerTwos/SoccerTwos-999826.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


library_name: ml-agents tags:

  • SoccerTwos
  • deep-reinforcement-learning
  • reinforcement-learning
  • ML-Agents-SoccerTwos

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: 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: miguepez/poca-SoccerTwos
  3. Step 2: Select your .nn /.onnx file
  4. Click on Watch the agent play 👀

Model info

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

Created: 2025-07-01

Updated: 2025-07-01

View on Hugging Face

Files (32)

.gitattributes
README.md
SoccerTwos.onnx ONNX
SoccerTwos/SoccerTwos-1499592.onnx ONNX
SoccerTwos/SoccerTwos-1499592.pt
SoccerTwos/SoccerTwos-1999972.onnx ONNX
SoccerTwos/SoccerTwos-1999972.pt
SoccerTwos/SoccerTwos-2499380.onnx ONNX
SoccerTwos/SoccerTwos-2499380.pt
SoccerTwos/SoccerTwos-2499951.onnx ONNX
SoccerTwos/SoccerTwos-2499951.pt
SoccerTwos/SoccerTwos-2607934.onnx ONNX
SoccerTwos/SoccerTwos-2607934.pt
SoccerTwos/SoccerTwos-499918.onnx ONNX
SoccerTwos/SoccerTwos-499918.pt
SoccerTwos/SoccerTwos-999826.onnx ONNX
SoccerTwos/SoccerTwos-999826.pt
SoccerTwos/checkpoint.pt
SoccerTwos/events.out.tfevents.1751304495.Migue.17704.0
SoccerTwos/events.out.tfevents.1751348259.Migue.7336.0
config.json
configuration.yaml
run_logs/Player-0.log
run_logs/Player-1.log
run_logs/Player-2.log
run_logs/Player-3.log
run_logs/Player-4.log
run_logs/Player-5.log
run_logs/Player-6.log
run_logs/Player-7.log
run_logs/timers.json
run_logs/training_status.json

Related models