ONNX Model Zoo

daishan986/poca-SoccerTwos

By daishan986 · ↓ 1 · ♥ 0 · Updated 2025-10-12

What's in this repo

This page lists the files in daishan986/poca-SoccerTwos, including SoccerTwos.onnx, SoccerTwos-0.onnx, SoccerTwos-1499618.onnx and more.

  • 13 ONNX models (.onnx files)
  • 67 files, including 32 .log, 15 .pt, 13 .onnx, 3 .json, 1 .md, 1 .0
  • Last updated 2025-10-12

ONNX files

File Size Download
SoccerTwos.onnx — Download
SoccerTwos/SoccerTwos-0.onnx — Download
SoccerTwos/SoccerTwos-1499618.onnx — Download
SoccerTwos/SoccerTwos-1499934.onnx — Download
SoccerTwos/SoccerTwos-48499995.onnx — Download
SoccerTwos/SoccerTwos-48999891.onnx — Download
SoccerTwos/SoccerTwos-49499933.onnx — Download
SoccerTwos/SoccerTwos-499391.onnx — Download
SoccerTwos/SoccerTwos-499540.onnx — Download
SoccerTwos/SoccerTwos-49999980.onnx — Download

Showing 10 of 13 .onnx files — see the full file list on the right.

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

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: daishan986/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
↓ 1 ♥ 0

Created: 2025-10-12

Updated: 2025-10-12

View on Hugging Face

Files (67)

.gitattributes
README.md
SoccerTwos.onnx ONNX
SoccerTwos/SoccerTwos-0.onnx ONNX
SoccerTwos/SoccerTwos-0.pt
SoccerTwos/SoccerTwos-1499618.onnx ONNX
SoccerTwos/SoccerTwos-1499618.pt
SoccerTwos/SoccerTwos-1499934.onnx ONNX
SoccerTwos/SoccerTwos-1499934.pt
SoccerTwos/SoccerTwos-1572932.pt
SoccerTwos/SoccerTwos-48499995.onnx ONNX
SoccerTwos/SoccerTwos-48499995.pt
SoccerTwos/SoccerTwos-48999891.onnx ONNX
SoccerTwos/SoccerTwos-48999891.pt
SoccerTwos/SoccerTwos-49499933.onnx ONNX
SoccerTwos/SoccerTwos-49499933.pt
SoccerTwos/SoccerTwos-499391.onnx ONNX
SoccerTwos/SoccerTwos-499391.pt
SoccerTwos/SoccerTwos-499540.onnx ONNX
SoccerTwos/SoccerTwos-499540.pt
SoccerTwos/SoccerTwos-49999980.onnx ONNX
SoccerTwos/SoccerTwos-49999980.pt
SoccerTwos/SoccerTwos-50000054.onnx ONNX
SoccerTwos/SoccerTwos-50000054.pt
SoccerTwos/SoccerTwos-81986.pt
SoccerTwos/SoccerTwos-999200.onnx ONNX
SoccerTwos/SoccerTwos-999200.pt
SoccerTwos/SoccerTwos-999708.onnx ONNX
SoccerTwos/SoccerTwos-999708.pt
SoccerTwos/checkpoint.pt
SoccerTwos/events.out.tfevents.1760262097.featurize.57603.0
config.json
configuration.yaml
run_logs/Player-0.log
run_logs/Player-1.log
run_logs/Player-10.log
run_logs/Player-11.log
run_logs/Player-12.log
run_logs/Player-13.log
run_logs/Player-14.log
run_logs/Player-15.log
run_logs/Player-16.log
run_logs/Player-17.log
run_logs/Player-18.log
run_logs/Player-19.log
run_logs/Player-2.log
run_logs/Player-20.log
run_logs/Player-21.log
run_logs/Player-22.log
run_logs/Player-23.log
run_logs/Player-24.log
run_logs/Player-25.log
run_logs/Player-26.log
run_logs/Player-27.log
run_logs/Player-28.log
run_logs/Player-29.log
run_logs/Player-3.log
run_logs/Player-30.log
run_logs/Player-31.log
run_logs/Player-4.log
run_logs/Player-5.log
run_logs/Player-6.log
run_logs/Player-7.log
run_logs/Player-8.log
run_logs/Player-9.log
run_logs/timers.json
run_logs/training_status.json

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