587건 · 관련도순
Maxim long-form brand story — engineered for commitment and mission alignment via StoryBrand + Hero's Journey + Emotional Arc Theory. Turns brand films into commitment mechanisms, not just awareness content.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Maxim fashion editorial video — engineered for aspirational desire and status signaling via Aesthetic Resonance + Aspirational Self + Social Comparison Theory. Fashion films that trigger status-driven purchase behavior.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Run 150+ AI apps via inference.sh CLI (infsh) — image generation, video creation, LLMs, search, 3D, social automation. Uses the terminal tool. Triggers: inference.sh, infsh, ai apps, flux, veo, image generation, video generation, seedream, seedance, tavily
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Delegate coding tasks to Blackbox AI CLI agent. Multi-model agent with built-in judge that runs tasks through multiple LLMs and picks the best result. Requires the blackbox CLI and a Blackbox AI API key.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Jailbreak LLMs: Parseltongue, GODMODE, ULTRAPLINIAN.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Designs robust function/tool calling schemas for LLMs with JSON schemas, validation strategies, typed interfaces, and example calls. Use when implementing "function calling", "tool use", "LLM tools", or "agent actions".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
AI/LLM security offensive checklist: prompt injection, jailbreaking, model extraction, training data poisoning, adversarial inputs, LLM-assisted attack automation, and AI system reconnaissance. Use when assessing AI/ML systems, red-teaming LLMs, or researching AI attack vectors.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
NTLM info disclosure is a Medium-severity finding when chained to context — the leak itself is intentional protocol behavior (RFC-compliant NTLMSSP challenge), but on internet-exposed enterprise infrastructure it provides exact reconnaissance for the next stage of an attack. Highest-value targets:
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Complete Open WebUI API integration for managing LLM models, chat completions, Ollama proxy operations, file uploads, knowledge bases (RAG), image generation, audio processing, and pipelines. Use this skill when interacting with Open WebUI instances via REST API - listing models, chatting with LLMs, uploading files for RAG, managing knowledge collections, or executing Ollama commands through the Open WebUI proxy. Requires OPENWEBUI_URL and OPENWEBUI_TOKEN environment variables or explicit parameters.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.