Reinforcement Learning
ml-agents
ONNX
unity-ml-agents
deep-reinforcement-learning
ML-Agents-Pyramids
Eval Results (legacy)
Instructions to use Preethi0205/MLAgents-Pyramids with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use Preethi0205/MLAgents-Pyramids with ml-agents:
mlagents-load-from-hf --repo-id="Preethi0205/MLAgents-Pyramids" --local-dir="./downloads"
- Notebooks
- Google Colab
- Kaggle
Add verified Deep RL course model evaluation for Unit 5 Part 2: Unity ML-Agents (ML-Agents-Pyramids)
ddddbaa verified |
Download README.md from Preethi0205/MLAgents-Pyramids: direct link, hf CLI and curl.
- Browser
- Download file 772 Bytes
-
https://huggingface.co/Preethi0205/MLAgents-Pyramids/resolve/main/README.md
- Command line
-
hf download hf://Preethi0205/MLAgents-Pyramids/README.md
-
curl -L -o README.md https://huggingface.co/Preethi0205/MLAgents-Pyramids/resolve/main/README.md
772 Bytes
| library_name: ml-agents | |
| tags: | |
| - unity-ml-agents | |
| - ml-agents | |
| - deep-reinforcement-learning | |
| - reinforcement-learning | |
| - ML-Agents-Pyramids | |
| model-index: | |
| - name: Pyramids | |
| results: | |
| - task: | |
| type: reinforcement-learning | |
| name: reinforcement-learning | |
| dataset: | |
| name: ML-Agents-Pyramids | |
| type: ML-Agents-Pyramids | |
| metrics: | |
| - type: mean_reward | |
| value: 2.10 +/- 0.40 | |
| name: mean_reward | |
| # **ppo** Agent playing **Pyramids** | |
| This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents) for Unit 5 Part 2 of the Deep RL Course. | |
| ## Evaluation Results | |
| - **Result**: 2.10 +/- 0.40 | |
| - **Threshold Required**: >= -100 | |
| - **Pass Status**: Passed ✅ | |