Reinforcement Learning
ml-agents
TensorBoard
ONNX
unity-ml-agents
deep-reinforcement-learning
ML-Agents-Pyramids
Instructions to use harikc456/PyramidsRND-ppo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use harikc456/PyramidsRND-ppo with ml-agents:
mlagents-load-from-hf --repo-id="harikc456/PyramidsRND-ppo" --local-dir="./downloads"
- Notebooks
- Google Colab
- Kaggle
Download config.json from harikc456/PyramidsRND-ppo: direct link, hf CLI and curl.
- Browser
- Download file 626 Bytes
-
https://huggingface.co/harikc456/PyramidsRND-ppo/resolve/main/config.json
- Command line
-
hf download hf://harikc456/PyramidsRND-ppo/config.json
-
curl -L -o config.json https://huggingface.co/harikc456/PyramidsRND-ppo/resolve/main/config.json
626 Bytes
| {"behaviors": {"Pyramids": {"trainer_type": "ppo", "hyperparameters": {"batch_size": 128, "buffer_size": 2048, "learning_rate": 0.0005, "beta": 0.01, "epsilon": 0.2, "lambd": 0.95, "num_epoch": 5, "learning_rate_schedule": "linear"}, "network_settings": {"normalize": false, "hidden_units": 512, "num_layers": 4, "vis_encode_type": "simple"}, "reward_signals": {"extrinsic": {"gamma": 0.99, "strength": 1.0}, "rnd": {"gamma": 0.99, "strength": 0.01, "network_settings": {"hidden_units": 64, "num_layers": 3}, "learning_rate": 0.0001}}, "keep_checkpoints": 5, "max_steps": 3000000, "time_horizon": 128, "summary_freq": 30000}}} |