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
Upload complete model and metadata for Unit 5 (Pyramids)
Browse files- Pyramids.onnx +3 -0
- README.md +27 -0
- configuration.yaml +3 -0
Pyramids.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:6c9d8cdde64777e731adb7cf45fe6346c97c14138ba9336a712e965b4c2b43bb
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size 8
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README.md
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---
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library_name: ml-agents
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tags:
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- ml-agents
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- tensorboard
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- onnx
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- unity-ml-agents
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- deep-reinforcement-learning
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- reinforcement-learning
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- ML-Agents-Pyramids
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model-index:
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- name: MLAgents-Pyramids
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results:
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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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metrics:
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- type: mean_reward
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value: 2.80 +/- 0.30
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name: mean_reward
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---
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# **PPO** Agent playing **Pyramids**
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This is a trained model of a **PPO** agent playing **Pyramids** using Unity ML-Agents.
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configuration.yaml
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behaviors:
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Pyramids:
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trainer_type: ppo
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