Reinforcement Learning
ml-agents
TensorBoard
ONNX
ML-Agents-Pyramids
deep-reinforcement-learning
unity-ml-agents
Eval Results (legacy)
Instructions to use RBhumi/ppo-Pyramids with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use RBhumi/ppo-Pyramids with ml-agents:
mlagents-load-from-hf --repo-id="RBhumi/ppo-Pyramids" --local-dir="./download: string[]s"
- Notebooks
- Google Colab
- Kaggle
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Download README.md from RBhumi/ppo-Pyramids: direct link, hf CLI and curl.
- Browser
- Download file 506 Bytes
-
https://huggingface.co/RBhumi/ppo-Pyramids/resolve/main/README.md
- Command line
-
hf download hf://RBhumi/ppo-Pyramids/README.md
-
curl -L -o README.md https://huggingface.co/RBhumi/ppo-Pyramids/resolve/main/README.md
506 Bytes
metadata
tags:
- reinforcement-learning
- ml-agents
- ML-Agents-Pyramids
- deep-reinforcement-learning
- unity-ml-agents
model-index:
- name: Pyramids
results:
- task:
type: reinforcement-learning
name: ML-Agents-Pyramids
dataset:
name: ML-Agents-Pyramids
type: reinforcement-learning
metrics:
- type: mean_reward
value: '0'
name: mean_reward
Pyramids
Trained Pyramids agent using Unity ML-Agents.
Environment: ML-Agents-Pyramids Library: ML-Agents