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pufferlib
【开发与工程】Version-aware guidance for PufferLib reinforcement-learning environments, vectorization, policies, PuffeRL training, evaluation, and safe checkpoint review. Covers the native 5.0 build and environment API, published 3.0.0 Gymnasium/PettingZoo adaptation, and a pinned historical 4.0 profile.
stable-baselines3
【效率与协作】Trains and evaluates single-agent reinforcement learning with Stable Baselines3 (PPO, SAC, DQN, TD3, DDPG, A2C), Gymnasium custom environments, vectorized rollouts, callbacks, and checkpoint normalization. Applies to reproducible RL experiments, continuous control, discrete actions, and SB3-Contrib recurrent or masked policies.
hugging-face-model-trainer
【部署与运维】Train or fine-tune language and vision models using TRL (Transformer Reinforcement Learning) or Unsloth with Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment.
linkedin-content-generator
【效率与协作】AI-powered LinkedIn content suite: generate posts, carousels, newsletters, and 30-day calendars with niche-specific SEO rules and a reinforcement-learning personal memory system.
trl-training
【效率与协作】Train and fine-tune transformer language models using TRL (Transformers Reinforcement Learning). Supports SFT, DPO, GRPO, KTO, RLOO and Reward Model training via CLI commands.
fine-tuning-with-trl
【效率与协作】Fine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment, PPO/GRPO for reward optimization, and reward model training. Use when need RLHF, align model with preferences, or train from human feedback. Works with HuggingFace Transformers.
verl-rl-training
【效率与协作】Provides guidance for training LLMs with reinforcement learning using verl (Volcano Engine RL). Use when implementing RLHF, GRPO, PPO, or other RL algorithms for LLM post-training at scale with flexible infrastructure backends.
huggingface-llm-trainer
【部署与运维】Train or fine-tune language and vision models using TRL (Transformer Reinforcement Learning) or Unsloth with Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validat…
trl-training
【开发与工程】Post-train LLMs with TRL (Transformers Reinforcement Learning) — SFT, DPO, GRPO, KTO, and reward-model training. Use when writing or debugging training code with the TRL Python API or the trl CLI.
finetuning
【部署与运维】Fine-tune models on Microsoft Foundry using SFT (supervised), DPO (preference), or RFT (reinforcement with graders). Covers dataset preparation, training job submission, deployment, and evaluation. USE FOR: fine-tune, SFT, DPO, RFT, training data, grader, distillation, fine-tuned model, training job, large file upload, calibrate grader, deploy fine-t…
self-optimization
【效率与协作】SONA self-optimizing neural architecture with ReasoningBank trajectory learning, EWC++ anti-forgetting, and reinforcement learning feedback loops.
reinforcement-learning-agents
【设计与创意】Design and train reinforcement learning agents — environment setup, reward shaping, policy gradient methods, and evaluation.
concrete-design-calculator
【设计与创意】Reinforced concrete design skill for flexure, shear, and serviceability calculations per ACI 318
bio-generative-design
【设计与创意】Designs novel molecules using REINVENT 4 (de novo, scaffold decoration, linker design, R-group, molecular optimization), MolMIM, Diffusion-based generators (DiGress, DiffSMol), and JT-VAE with explicit handling of multi-parameter optimization (MPO), goal-directed scoring functions, transfer/reinforcement/curriculum learning, synthetic accessibility s…
cross-regulatory-impact-analyzer-patrick-munro
【数据与研究】Analyzes how multiple regulations interact for a specific product, service, or business model. Identifies where obligations overlap, reinforce, complement, duplicate, or conflict; builds a priority matrix; produces an integrated compliance timeline; and estimates the total compliance burden. Use when (1) scoping a new product or service against the f…
optim-agent
【效率与协作】Use when the user wants to optimize configurable system parameters against a measurable scalar objective, especially for model training, inference, quantitative strategies, reinforcement learning, scientific workflows, or other expensive black-box evaluations where reading the project can improve trial selection.
monte-carlo-reinforce-agent
【开发与工程】Reinforces an AI agent by turning Monte Carlo's reinforcement loop diagnosis into code fixes. Reads the daily reinforcement loop report for an agent's workflows, ranks the diagnosed issues, proposes what to fix, and — with the user's approval at each step — opens a pull request. Activates on "fix my agent", "improve my agent's health", "reinforce my …
closer-sales-script
【开发与工程】Produce and run a word-for-word gym intro-consult script using the CLOSER sequence (Clarify, Label, Overview, Sell, Explain, Reinforce) to take a booked lead to a paid membership. Use when a gym owner or coach asks for a sales script, says "how do I close the consult", "intro consult", "no-sweat consult", "CLOSER framework", "present the price", "I'm…