70-deployment-serving
Create your model-serving skill from Ollama documentation before learning deployment theory
npx skills add majiayu000/claude-skill-registry --skill 70-deployment-serving --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Build Your Model Serving Skill You have a fine-tuned model from Chapter 69. Now you need to deploy it so real users can interact with it. But here is the pattern that separates effective AI-native developers from those who struggle: **build your skill first, then learn the technology**. In traditional learning, you study deployment options, configure servers, troubleshoot errors, and hope you remember the patterns later. In Skill-First learning, you create a reusable intelligence asset before you even understand the technology deeply. This asset grows with you as you learn, and by the end of the chapter, you own a production-ready skill you can sell or deploy. This lesson follows the same pattern you used in Part 6, Part 7, and earlier Part 8 chapters. Clone a fresh skills-lab, fetch official documentation, and build your `model-serving` skill from authoritative sources rather than memory. ## Why Skill-First for Model Serving? Model serving involves multiple components: export formats (GGUF, safetensors), quantization levels (Q4_K_M, Q8_0), inference servers (Ollama, vLLM), and performance tuning (batch sizes, context lengths, memory management). Trying to memorize all configurat
- Why Skill-First for Model Serving?
- Step 1: Clone a Fresh Skills-Lab
- Step 2: Write Your LEARNING-SPEC.md
- Step 3: Fetch Official Documentation
- Step 4: Create Your model-serving Skill
- Step 5: Verify Your Skill
- What Happens Next
- Try With AI
- Prompt 1: Verify Skill Structure
- Prompt 2: Connect to Your Hardware
- Prompt 3: Validate Against Official Docs
- Safety Note
Clone the skills-lab repository git clone https://github.com/panaversity/skills-lab.git ~/skills-lab-ch70 Navigate to the directory cd ~/skills-lab-ch70 Create the skill directory structure mkdir -p .claude/skills/model-serving Check the skill exists ls -la .claude/skills/model-serving/ View the skill content head -50 .claude/skills/model-serving/SKILL.md
What does the 70-deployment-serving skill do?
Create your model-serving skill from Ollama documentation before learning deployment theory
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill 70-deployment-serving --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.