Reinforcement Learning
ml-agents
ONNX
ML-Agents-SnowballTarget
ppo
deep-rl-course
Eval Results (legacy)
Instructions to use rohit0128/ppo-SnowballTarget with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use rohit0128/ppo-SnowballTarget with ml-agents:
mlagents-load-from-hf --repo-id="rohit0128/ppo-SnowballTarget" --local-dir="./downloads"
- Notebooks
- Google Colab
- Kaggle
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Download README.md from rohit0128/ppo-SnowballTarget: direct link, hf CLI and curl.
- Browser
- Download file 985 Bytes
-
https://huggingface.co/rohit0128/ppo-SnowballTarget/resolve/main/README.md
- Command line
-
hf download hf://rohit0128/ppo-SnowballTarget/README.md
-
curl -L -o README.md https://huggingface.co/rohit0128/ppo-SnowballTarget/resolve/main/README.md
985 Bytes
| library_name: ml-agents | |
| tags: | |
| - ML-Agents-SnowballTarget | |
| - ppo | |
| - ml-agents | |
| - reinforcement-learning | |
| - deep-rl-course | |
| model-index: | |
| - name: ppo-SnowballTarget | |
| results: | |
| - task: | |
| type: reinforcement-learning | |
| name: reinforcement-learning | |
| dataset: | |
| name: ML-Agents-SnowballTarget | |
| type: ML-Agents-SnowballTarget | |
| metrics: | |
| - type: mean_reward | |
| value: "15.00 +/- 1.00" | |
| name: mean_reward | |
| # ppo-SnowballTarget | |
| This is a trained model of a **PPO** agent playing **ML-Agents-SnowballTarget**. | |
| This model was trained as part of the **Hugging Face Deep Reinforcement Learning Course**. | |
| ## Evaluation Results | |
| - **Environment**: `ML-Agents-SnowballTarget` | |
| - **Algorithm**: `PPO` | |
| - **Library**: `ml-agents` | |
| - **Mean Reward**: `15.00 +/- 1.00` | |
| ## Usage | |
| To evaluate this model locally or play with it, download the model files from this repository. | |