1,594 boosters for "ai" — open source, verified from GitHub, ready to install
Finds the best models for a task by querying official HF benchmark leaderboards, enriching results with model size data, filtering for what fits on the user's device, and returning a comparison table with benchmark scores.
Trackio is an experiment tracking library for logging and visualizing ML training metrics. It syncs to Hugging Face Spaces for real-time monitoring dashboards. Use in your training scripts to log metrics: → See references/logging_metrics.md for setup, TRL integration, and configuration options.
Rules and patterns for ML demos on Hugging Face Spaces with ZeroGPU hardware. Covers , duration and quota tuning, process isolation, the CUDA availability model, concurrency safety, and CUDA build constraints. This skill is for Gradio SDK Spaces using ZeroGPU hardware. Docker and Static Spaces canno
Hugging Face Spaces host machine-learning applications. There are 1M+ today; each Space is a git repo. This skill covers creating, building, debugging, and maintaining them. Before anything else: 1. Check the CLI is installed: . If not, .
Hugging Face Paper pages (hf.co/papers) is a platform built on top of arXiv (arxiv.org), specifically for research papers in the field of artificial intelligence (AI) and computer science. Hugging Face users can submit their paper at hf.co/papers/submit, which features it on the Daily Papers feed (h
Transformers.js enables running state-of-the-art machine learning models directly in JavaScript, both in browsers and Node.js environments, with no server required. Use this skill when you need to: The pipeline API is the easiest way to use models. It groups together preprocessing, model inference,
"name": "huggingface-skills", "description": "Agent Skills for AI/ML tasks including dataset creation, model training, evaluation, and research paper publishing on Hugging Face Hub", "name": "Hugging Face"
Fast, calibration-free weight quantization supporting 8/4/3/2/1-bit precision with multiple optimized backends. HQQ uses to define quantization parameters: The core quantized layer that replaces :
A skill that enables researchers and AI engineers to publish, manage, and link research papers on Hugging Face Hub with arXiv integration and professional markdown generation. Useful for academics and ML practitioners looking to streamline paper publication workflows.
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.
Trackio is an ML experiment tracking library that integrates with Hugging Face to log metrics, visualize training progress, and trigger alerts during model development. It's useful for ML engineers and researchers who need real-time monitoring and experiment management.
A skill that generates reusable command-line scripts for automating Hugging Face API interactions, useful for developers who need to repeatedly fetch, process, or chain API calls.
A multi-agent orchestration system for Claude Code that enables complex agentic workflows through a CLI and MCP server interface. Useful for developers building sophisticated AI-powered automation and coordinated agent systems within Claude's ecosystem.
1. Fetch homepage HTML (curl or WebFetch) 2. Detect business type (SaaS, Local, E-commerce, Publisher, Agency, Other) 3. Extract key pages from sitemap.xml or internal links (up to 50 pages)
Generates per-category catalog JSON files from the npm package's public API. Each catalog lists all UseCase and EventHandler abstractions in a category with their resolved source file paths. LLMs read source files on demand for exact, up-to-date types — no enrichment phase needed. 1. Discovers all
"description": "Developer experience essentials: GitHub Actions debugging, conversation cloning/half-cloning, context handoffs, and Reddit research via Gemini CLI", "version": "0.14.12", "email": "yoyoyosss@wearehackerone.com"
"description": "Agent Team & Skill Architect — Meta-skill that designs agent teams, defines specialized agents, and generates skills for your domain/project. 도메인/프로젝트에 맞는 하네스를 구성하고, 전문 에이전트를 정의하며, 에이전트가 사용할 스킬을 생성하는 메타 스킬.", "url": "https://github.com/revfactory" "homepage": "https://github.com/revf
Agents are the agentic logic layer of OpenJarvis. They determine how a query is processed -- whether it goes directly to a model, through a tool-calling loop, via ReAct reasoning, CodeAct code execution, recursive decomposition, or an external agent runtime. All agents implement the ABC and are reg
"name": "cursor-talk-to-figma-mcp", "description": "Cursor Talk to Figma MCP", "module": "dist/server.js",
IntentKit is an open-source, self-hosted cloud agent cluster that manages a collaborative team of AI agents for you.
You are the ZCF Template Engine Specialist for the ZCF (Zero-Config Code Flow) project.
You are the ZCF i18n Specialist for the ZCF (Zero-Config Code Flow) project.
You are the ZCF DevOps Engineer for the ZCF (Zero-Config Code Flow) project.
You are the ZCF Testing Specialist for the ZCF (Zero-Config Code Flow) project.
