Reinforcement Learning
ml-agents
ONNX
SnowballTarget
deep-reinforcement-learning
ML-Agents-SnowballTarget
Eval Results (legacy)
Instructions to use Preethi0205/ppo-SnowballTarget with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use Preethi0205/ppo-SnowballTarget with ml-agents:
mlagents-load-from-hf --repo-id="Preethi0205/ppo-SnowballTarget" --local-dir="./downloads"
- Notebooks
- Google Colab
- Kaggle
Add verified Deep RL course model evaluation for Unit 5 Part 1: Unity ML-Agents (ML-Agents-SnowballTarget)
648b024 verified |
Download README.md from Preethi0205/ppo-SnowballTarget: direct link, hf CLI and curl.
- Browser
- Download file 809 Bytes
-
https://huggingface.co/Preethi0205/ppo-SnowballTarget/resolve/main/README.md
- Command line
-
hf download hf://Preethi0205/ppo-SnowballTarget/README.md
-
curl -L -o README.md https://huggingface.co/Preethi0205/ppo-SnowballTarget/resolve/main/README.md
809 Bytes
| library_name: ml-agents | |
| tags: | |
| - SnowballTarget | |
| - deep-reinforcement-learning | |
| - reinforcement-learning | |
| - ml-agents | |
| - ML-Agents-SnowballTarget | |
| model-index: | |
| - name: SnowballTarget | |
| results: | |
| - task: | |
| type: reinforcement-learning | |
| name: reinforcement-learning | |
| dataset: | |
| name: ML-Agents-SnowballTarget | |
| type: ML-Agents-SnowballTarget | |
| metrics: | |
| - type: mean_reward | |
| value: 42.50 +/- 4.20 | |
| name: mean_reward | |
| # **ppo** Agent playing **SnowballTarget** | |
| This is a trained model of a **ppo** agent playing **SnowballTarget** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents) for Unit 5 Part 1 of the Deep RL Course. | |
| ## Evaluation Results | |
| - **Result**: 42.50 +/- 4.20 | |
| - **Threshold Required**: >= -100 | |
| - **Pass Status**: Passed ✅ | |