Reinforcement Learning
ml-agents
ONNX
Pyramids
deep-reinforcement-learning
ML-Agents-Pyramids
Eval Results (legacy)
Instructions to use Karthik32/ML-Agents-Pyramids with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use Karthik32/ML-Agents-Pyramids with ml-agents:
mlagents-load-from-hf --repo-id="Karthik32/ML-Agents-Pyramids" --local-dir="./downloads"
- Notebooks
- Google Colab
- Kaggle
Add model card with evaluation metrics
Browse files
README.md
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---
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library_name: ml-agents
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tags:
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- Pyramids
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- deep-reinforcement-learning
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- reinforcement-learning
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- ml-agents
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- ML-Agents-Pyramids
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model-index:
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- name: ML-Agents-Pyramids
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results:
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- metrics:
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- type: mean_reward
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value: 12.00 +/- 0.00
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name: mean_reward
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task:
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type: reinforcement-learning
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name: reinforcement-learning
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dataset:
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name: ML-Agents-Pyramids
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type: ML-Agents-Pyramids
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---
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# Unity ML-Agents - Pyramids
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This is a trained model of an agent playing **Pyramids** using Unity ML-Agents.
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Trained for Unit 5 of the Hugging Face Deep Reinforcement Learning Course.
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