Reinforcement Learning
ml-agents
ONNX
ML-Agents-SnowballTarget
SnowballTarget
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use SimhaSimha/ppo-SnowballTarget with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use SimhaSimha/ppo-SnowballTarget with ml-agents:
mlagents-load-from-hf --repo-id="SimhaSimha/ppo-SnowballTarget" --local-dir="./download: string[]s"
- Notebooks
- Google Colab
- Kaggle
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Download README.md from SimhaSimha/ppo-SnowballTarget: direct link, hf CLI and curl.
- Browser
- Download file 809 Bytes
-
https://huggingface.co/SimhaSimha/ppo-SnowballTarget/resolve/main/README.md
- Command line
-
hf download hf://SimhaSimha/ppo-SnowballTarget/README.md
-
curl -L -o README.md https://huggingface.co/SimhaSimha/ppo-SnowballTarget/resolve/main/README.md
809 Bytes
metadata
library_name: ml-agents
tags:
- ML-Agents-SnowballTarget
- SnowballTarget
- ml-agents
- reinforcement-learning
- deep-reinforcement-learning
model-index:
- name: ppo-SnowballTarget
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: ML-Agents-SnowballTarget
type: ML-Agents-SnowballTarget
metrics:
- type: mean_reward
value: 25.50 +/- 2.10
name: mean_reward
ppo Agent playing SnowballTarget
This is a trained model of a ppo agent playing SnowballTarget using the Unity ML-Agents Library. To learn more check Unit 5 of the Deep Reinforcement Learning Course: https://huggingface.co/deep-rl-course/unit5/introduction