zikangzheng/poca-SoccerTwos
By zikangzheng · ↓ 0 · ♥ 0 · Updated 2025-11-05
What's in this repo
This page lists the files in zikangzheng/poca-SoccerTwos, including SoccerTwos.onnx, SoccerTwos-18499950.onnx, SoccerTwos-18999204.onnx and more.
- 13 ONNX models (.onnx files)
- 34 files, including 13 .onnx, 13 .pt, 3 .json, 1 .md, 1 .0, 1 .yaml
- Last updated 2025-11-05
ONNX files
| File | Size | Download |
|---|---|---|
| SoccerTwos.onnx | — | Download |
| SoccerTwos/SoccerTwos-18499950.onnx | — | Download |
| SoccerTwos/SoccerTwos-18999204.onnx | — | Download |
| SoccerTwos/SoccerTwos-18999916.onnx | — | Download |
| SoccerTwos/SoccerTwos-19499040.onnx | — | Download |
| SoccerTwos/SoccerTwos-19499852.onnx | — | Download |
| SoccerTwos/SoccerTwos-19999226.onnx | — | Download |
| SoccerTwos/SoccerTwos-19999810.onnx | — | Download |
| SoccerTwos/SoccerTwos-20000332.onnx | — | Download |
| SoccerTwos/SoccerTwos-20499993.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
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
- If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity
- Step 1: Find your model_id: zikangzheng/poca-SoccerTwos
- Step 2: Select your .nn /.onnx file
- Click on Watch the agent play 👀
Model info
Created: 2025-11-05
Updated: 2025-11-05
View on Hugging Face