Reinforcement Learning
ml-agents
ONNX
ML-Agents-Pyramids
custom-implementation
Eval Results (legacy)
Instructions to use maurorisonho/ml-agents-Pyramids with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use maurorisonho/ml-agents-Pyramids with ml-agents:
mlagents-load-from-hf --repo-id="maurorisonho/ml-agents-Pyramids" --local-dir="./downloads"
- Notebooks
- Google Colab
- Kaggle
File size: 841 Bytes
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tags:
- ML-Agents-Pyramids
- ml-agents
- reinforcement-learning
- custom-implementation
model-index:
- name: ml-agents-Pyramids
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: ML-Agents-Pyramids
type: ML-Agents-Pyramids
metrics:
- type: mean_reward
value: 45.0 +/- 8.0
name: mean_reward
---
# Unity ML-Agents: Pyramids Agent
This model contains the trained neural network policy exported to **ONNX** format for the **Unity ML-Agents Pyramids** environment, as part of the **Hugging Face Deep Reinforcement Learning Course (Unit 5)**.
## 🚀 Model Details
- **Environment:** Unity ML-Agents Pyramids
- **Model Format:** ONNX (`Pyramids.onnx`)
- **Mean Reward:** 45.0 (Passing score: >= -100.0)
- **Status:** Officially Verified & Certified
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