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Local LLM deployment with Ollama and Open WebUI v1.0.0

Use this resource to run language models locally

New

  • 320 downloads
  • 167 likes
  • 134 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install local-llm-ollama-deployment

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent sets up a local environment with Ollama and Open WebUI: installation, server start, model download and runs, GPU-specific tuning. Container images and model revisions must be pinned and reviewed before use.

Mostly picked by

Updated November 2, 2026

Card for the “Local LLM deployment with Ollama and Open WebUI” skill

Details

Works in
Install guides
Generates with
Your agent's model
Licence
MIT

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What you get

  • SKILL.md: installation, server start and model download
  • SKILL.md: quantization choices and hardware limits

Good fit for

  • You want to test models without sending your data to the cloud
  • You prepare a shared inference endpoint for a small team

Not for

    Tags

    • ollama
    • local llm
    • gpu
    • open webui
    • inference

    About

    You say

    “Install Ollama and a 7-billion-parameter model on my PC with an Nvidia GPU.”

    Card for the “Local LLM deployment with Ollama and Open WebUI” skill

    Skill published by sickn33 under the MIT license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to run language models locally
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • SKILL.md11 KB

    Origin and licence

    Listed unmodified

    Author
    sickn33
    Source
    github.com/sickn33/agentic-awesome-skills/tree/e9809578fd426a284af017c5db99f8eb6628e6ca/skills/ollama-stack
    Licence
    MIT

    Notice

    « ollama-stack » (sickn33, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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