Reinforcement Learning
ml-agents
TensorBoard
ONNX
ML-Agents-SnowballTarget
deep-reinforcement-learning
unity-ml-agents
Eval Results (legacy)
Instructions to use MUTTERAHUL/ppo-SnowballTarget with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use MUTTERAHUL/ppo-SnowballTarget with ml-agents:
mlagents-load-from-hf --repo-id="MUTTERAHUL/ppo-SnowballTarget" --local-dir="./downloads"
- Notebooks
- Google Colab
- Kaggle
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Download README.md from MUTTERAHUL/ppo-SnowballTarget: direct link, hf CLI and curl.
- Browser
- Download file 650 Bytes
-
https://huggingface.co/MUTTERAHUL/ppo-SnowballTarget/resolve/main/README.md
- Command line
-
hf download hf://MUTTERAHUL/ppo-SnowballTarget/README.md
-
curl -L -o README.md https://huggingface.co/MUTTERAHUL/ppo-SnowballTarget/resolve/main/README.md
650 Bytes
metadata
tags:
- ml-agents
- ML-Agents-SnowballTarget
- reinforcement-learning
- deep-reinforcement-learning
- unity-ml-agents
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: ML-Agents-SnowballTarget
type: ML-Agents-SnowballTarget
metrics:
- type: mean_reward
value: 10.00 +/- 2.00
name: mean_reward
verified: false
PPO Agent playing ML-Agents-SnowballTarget
This is a trained model of a PPO agent playing ML-Agents-SnowballTarget for the Hugging Face Deep Reinforcement Learning Course.