175 boosters for "har" — open source, verified from GitHub, ready to install
This skill is for running evaluations against models on the Hugging Face Hub on local hardware. It does not cover: If the user wants to run the same eval remotely on Hugging Face Jobs, hand off to the skill and pass it one of the local scripts in this skill.
Tiebreakers when the request is ambiguous: "embedding model" / "vector search" / "similarity" → [SentenceTransformer]. "rerank" / "ranker" / "two-stage" → [CrossEncoder]. "SPLADE" / "sparse" / "inverted index" → [SparseEncoder]. If still unclear, ask. Override only if the user specifies otherwise: T
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, .
Build and publish a Gradio demo on Hugging Face Spaces that runs inference with a user-provided LoRA. Use whenever someone asks to create, generate, ship, or publish "a Space", "a demo", "a Gradio app", or "a playground" for a LoRA — whether the base model is Qwen-Image, Qwen-Image-Edit, LTX, or ano
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
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
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 :
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.
"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
❶ One is a new React framework - target web and native with a single Vite plugin and fully shared code, so you can ship cross-platform nearly as easy as single-platform.
Heuristic scoring (no AI key configured).
"name": "designlang", "description": "Extract any website's design language and ship it. Eleven slash commands \u2014 /extract, /site, /grade, /battle, /remix, /pack, /theme-swap, /brand, /pair, /studio, /verify \u2014 wrap the designlang CLI to pull DTCG tokens, Tailwind/shadcn/Figma vars, motion +
Try these methods in order. Use the first one available: If is wired as a SessionStart hook in , is injected into context automatically at session start. Skip step 1 below. To wire it: or run .
.env files built for sharing powered by @env-spec decorator comments
Connect a Kubernetes cluster (EKS, GKE, AKS, or KOPS) to CAST AI for cost optimization, autoscaling, and security scanning. Covers API key generation, Helm chart installation of the CAST AI agent, and Terraform provider setup. Log in to https://console.cast.ai and navigate to API > API Access Keys.
你是一位中国传统四柱八字命理的专业研究者。你熟读以下经典典籍：《穷通宝典》、《三命通会》、《滴天髓》、《渊海子平》、《千里命稿》、《协纪辨方书》、《果老星宗》、《子平真诠》、《神峰通考》。 本 skill 指导你通过交互式步骤收集用户信息，然后进行专业的八字排盘与分析。 排盘和分析过程中，需要查阅以下参考文件获取详细规则和表格数据：
Author professional HTML presentations as static files. One theme file = one look. One layout file = one page type. One animation class = one entry effect. All pages share a token-based design system in .
"description": "Cloud-backed persistent memory powered by Deeplake — read, write, and share memory across Claude Code sessions and agents", "version": "0.7.104", "name": "Activeloop",
This project uses a portable brain in . It is authoritative for memory, skills, and protocols. For deploy / ship / release / migration / schema / timestamp / timezone /
These instructions guide GitHub Copilot on how to generate and modify code for the project. State Machine Cat is a tool for visualizing state charts. It parses state machine descriptions and renders them as diagrams. Tests must be created for all new functionality using Mocha and Node's assert modu
You are a trading strategy hypothesis ideation engine. Produce 1-5 falsifiable hypothesis cards from structured evidence.
Browse once, cache the APIs, reuse them instantly. First call discovers and learns the site's APIs (~20-80s). Every subsequent call uses cached skills (<200ms for server-fetch, ~2s for sites requiring browser execution). When the task touches docs, install guidance, eval claims, landing-page copy, r
