Reinforcement Learning
ml-agents
TensorBoard
ONNX
Pyramids
deep-reinforcement-learning
ML-Agents-Pyramids
Instructions to use AnnaMats/ppo-Pyramids-Training with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use AnnaMats/ppo-Pyramids-Training with ml-agents:
mlagents-load-from-hf --repo-id="AnnaMats/ppo-Pyramids-Training" --local-dir="./download: string[]s"
- Notebooks
- Google Colab
- Kaggle
| #!/usr/bin/env python3 | |
| import argparse | |
| import subprocess | |
| if __name__ == "__main__": | |
| # markdown-link-check doesn't support multiple files on the commandline, so this hacks around that. | |
| # Note that you must install the package separately via npm. For example: | |
| # brew install npm; npm install -g markdown-link-check | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument("--check-remote", action="store_true") | |
| parser.add_argument("files", nargs="*") | |
| args = parser.parse_args() | |
| config_file = ( | |
| "markdown-link-check.full.json" | |
| if args.check_remote | |
| else "markdown-link-check.fast.json" | |
| ) | |
| for f in args.files: | |
| subprocess_args = ["markdown-link-check", "-q", "-c", config_file, f] | |
| subprocess.check_call(subprocess_args) | |