Reinforcement Learning
ml-agents
ONNX
TensorBoard
unity-ml-agents
deep-reinforcement-learning
ML-Agents-Pyramids
Eval Results (legacy)
Instructions to use NPC007/MLAgents-Pyramids with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use NPC007/MLAgents-Pyramids with ml-agents:
mlagents-load-from-hf --repo-id="NPC007/MLAgents-Pyramids" --local-dir="./downloads"
- Notebooks
- Google Colab
- Kaggle
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Download README.md from NPC007/MLAgents-Pyramids: direct link, hf CLI and curl.
- Browser
- Download file 583 Bytes
-
https://huggingface.co/NPC007/MLAgents-Pyramids/resolve/main/README.md
- Command line
-
hf download hf://NPC007/MLAgents-Pyramids/README.md
-
curl -L -o README.md https://huggingface.co/NPC007/MLAgents-Pyramids/resolve/main/README.md
583 Bytes
metadata
library_name: ml-agents
tags:
- ml-agents
- tensorboard
- onnx
- unity-ml-agents
- deep-reinforcement-learning
- reinforcement-learning
- ML-Agents-Pyramids
model-index:
- name: MLAgents-Pyramids
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: ML-Agents-Pyramids
type: ML-Agents-Pyramids
metrics:
- type: mean_reward
value: 2.80 +/- 0.30
name: mean_reward
PPO Agent playing Pyramids
This is a trained model of a PPO agent playing Pyramids using Unity ML-Agents.