11 boosters for "persistence" — open source, verified from GitHub, ready to install
Train object detection, image classification, and SAM/SAM2 segmentation models on managed cloud GPUs. No local GPU setup required—results are automatically saved to the Hugging Face Hub. Use this skill when users want to: Helper scripts use PEP 723 inline dependencies. Run them with :
Train language models using TRL (Transformer Reinforcement Learning) on fully managed Hugging Face infrastructure. No local GPU setup required—models train on cloud GPUs and results are automatically saved to the Hugging Face Hub. Use this skill when users want to: Use Unsloth () instead of standard
Run any workload on fully managed Hugging Face infrastructure. No local setup required—jobs run on cloud CPUs, GPUs, or TPUs and can persist results to the Hugging Face Hub. Use this skill when users want to: When assisting with jobs:
A skill for fine-tuning and training language models on Hugging Face's cloud GPU infrastructure using TRL, supporting SFT, DPO, GRPO methods and GGUF conversion for local deployment. Developers and ML engineers working with cloud-based model training benefit from this comprehensive guidance.
This skill enables users to run Python workloads, Docker jobs, and GPU-intensive tasks on Hugging Face's managed infrastructure without local setup. It's valuable for ML engineers, data scientists, and developers needing cloud compute for training, inference, and batch processing.
A Cursor IDE rules booster providing React best practices and patterns for building modern web applications with functional components, hooks, and state management guidance.
This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on 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 validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence. Should be invoked for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.
"version": "0.14.4", "description": "Persistent memory system for AI coding assistants. Captures decisions, learnings, and context from coding sessions and surfaces them when relevant.", "name": "Robert Allen",
agent-builder enables developers to create production-ready AI agents with pai-agent-sdk and Pydantic AI, including tools configuration, session persistence, and hierarchical agent setups. Ideal for building autonomous applications, chatbots, and HITL workflows.
A data architecture agent that guides developers through implementing robust data persistence using Room ORM, SQLite, and secure storage patterns for Android and desktop applications. Ideal for developers building apps that require reliable local data management with encryption and schema migrations.
This MCP server enables AI-driven WordPress content creation with advanced features like automated SEO optimization, image hosting, and one-click publishing. It's useful for content creators, bloggers, and WordPress developers who want to streamline their publishing workflow with AI assistance.
