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Llm Fine Tuning

Checked
omer-metin·vlatest·ai-ml·Apache-2.0

Provides LLMs guidance and assistance for building AI and machine learning applications.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add omer-metin/skills-for-antigravity --skill llm-fine-tuning -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

omer-metin

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Install target

Live repository

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No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

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  • No pipe-to-shell installers: passed

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    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned omer-metin/skills-for-antigravity at e8dcf4e873.

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Commit
e8dcf4e873
Manifest
skills/llm-fine-tuning/SKILL.md
Scanned
4 files, 586 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
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About this skill

What it does

This skill allows you to fine-tune Large Language Models (LLMs) for specific tasks or domains. It adapts a pre-trained LLM using your own dataset, improving its performance on targeted applications. The resulting model exhibits enhanced accuracy and relevance compared to the base model when dealing with similar inputs.

When to use it

  • Specialized Content Generation: Generate marketing copy tailored to a specific brand voice or style.
  • Improved Question Answering: Create an AI assistant that excels at answering questions related to a niche subject area, like legal documents or medical records.
  • Code Generation for Specific Frameworks: Fine-tune a model to generate code snippets optimized for a particular programming framework or library.
  • Data Extraction and Summarization: Train the LLM to extract specific data points from unstructured text or create concise summaries of lengthy reports.

Key capabilities

  • Dataset preparation and formatting
  • Model selection based on task requirements
  • Hyperparameter tuning for optimal performance
  • Evaluation metrics tracking during training
  • Deployment of fine-tuned models

Example prompts

  • "Fine-tune this LLM using the provided dataset of customer service transcripts to improve response quality."
  • "Train a model to generate Python code snippets based on these examples, focusing on Django framework usage."
  • “Can you adapt this base model with my legal document corpus?”

Tips & gotchas

  • Requires a curated and representative training dataset for best results. The quality of the data directly impacts the fine-tuned model's performance.