Reinforcement Learning
ml-agents
TensorBoard
ONNX
unity-ml-agents
deep-reinforcement-learning
ML-Agents-Pyramids
Eval Results (legacy)
Instructions to use yojitha/MLAgents-Pyramids with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use yojitha/MLAgents-Pyramids with ml-agents:
mlagents-load-from-hf --repo-id="yojitha/MLAgents-Pyramids" --local-dir="./downloads"
- Notebooks
- Google Colab
- Kaggle
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Download README.md from yojitha/MLAgents-Pyramids: direct link, hf CLI and curl.
- Browser
- Download file 869 Bytes
-
https://huggingface.co/yojitha/MLAgents-Pyramids/resolve/main/README.md
- Command line
-
hf download hf://yojitha/MLAgents-Pyramids/README.md
-
curl -L -o README.md https://huggingface.co/yojitha/MLAgents-Pyramids/resolve/main/README.md
869 Bytes
metadata
library_name: ml-agents
tags:
- unity-ml-agents
- 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: 10.00 +/- 0.00
name: mean_reward
MLAgents-Pyramids
Trained ML-Agents agent playing Pyramids for Hugging Face Deep RL Course Unit 5.
This model was trained as part of the Hugging Face Deep Reinforcement Learning Course.
Model Details
- User: yojitha
- Course Unit: Unit 5b
- Task: Reinforcement Learning