Reinforcement Learning
ml-agents
ONNX
ML-Agents-Pyramids
unity-ml-agents
deep-rl-course
Eval Results (legacy)
Instructions to use rajurk11/ppo-Pyramids with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use rajurk11/ppo-Pyramids with ml-agents:
mlagents-load-from-hf --repo-id="rajurk11/ppo-Pyramids" --local-dir="./downloads"
- Notebooks
- Google Colab
- Kaggle
|
Download README.md from rajurk11/ppo-Pyramids: direct link, hf CLI and curl.
- Browser
- Download file 571 Bytes
-
https://huggingface.co/rajurk11/ppo-Pyramids/resolve/main/README.md
- Command line
-
hf download hf://rajurk11/ppo-Pyramids/README.md
-
curl -L -o README.md https://huggingface.co/rajurk11/ppo-Pyramids/resolve/main/README.md
571 Bytes
metadata
tags:
- ML-Agents-Pyramids
- ml-agents
- reinforcement-learning
- unity-ml-agents
- deep-rl-course
model-index:
- name: ppo-Pyramids
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: ML-Agents-Pyramids
type: ML-Agents-Pyramids
metrics:
- type: mean_reward
value: 18.50 +/- 1.50
name: mean_reward
PPO Agent playing ML-Agents-Pyramids
This is a trained PPO model for ML-Agents-Pyramids trained as part of the Hugging Face Deep RL Course.