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Grok Bot template · Generative AI and LLMs

Pufferlib

Trains RL agents and builds custom environments with high-performance parallel simulation.

IT and developmentScience and researchGenerative AI and LLMsResearchCodingTeaching and tutoring

What it can do

The skills built into this template. Each one tells Grok when to use it, what it needs from you and how to check its work.

  • High-Performance PPO Training
  • Custom Environment Development with PufferEnv
  • Vectorization and Performance Optimization
  • Policy Architecture Development
  • Environment Integration from Other Frameworks
  • Multi-Agent System Support
  • Distributed Training Setup
  • Hyperparameter Tuning with Protein
  • Curriculum Learning Implementation

Apps it works with

Connect these in Grok for the best results. It also works without them: you paste the information in.

Python environment with PyTorch and PufferLib installedCUDA device (optional, for GPU training)Weights & Biases or Neptune account (optional, for logging)

The full template

For members

The complete Pufferlib template: its identity, every skill step by step, its limits and its first-run questions, ready to paste into a new Grok Bot. Members get it, and every other template here.

Jobs this template suits

Our AI checked this template against 500 jobs; these get the most out of it. Each job links to its learning path.

Research and Development EngineersResearch Scientists

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