Individual skill
llm-fine-tuning
Set up infrastructure for fine-tuning LLMs with QLoRA, LoRA, and full fine-tuning using Hugging Face TRL, Axolotl, and distributed training with DeepSpeed or FSDP. Covers dataset prep, training runs, and model export.
infrastructure/local-ai/llm-fine-tuning/SKILL.md
Source commit 0365f57a079b1332f95cf26e31dd2d5332a8399f
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Network or broad shell
- Last checked
- Nov 10, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 1,198
- Repository last updated
- May 22, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- agent-skills Repository topic
- agentic-ai Repository topic
- ai-agents Repository topic
- cheatsheets Repository topic
- devops Repository topic
- infrastructure-as-code Repository topic
- kubernetes Repository topic
- security Repository topic
- sre Repository topic
- terraform Repository topic
- devops Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
Read excerpt
# LLM Fine-Tuning Infrastructure
Train and fine-tune open-source LLMs efficiently — from LoRA on a single GPU to distributed full fine-tuning across multi-node clusters.
## When to Use This Skill
Use this skill when:
- Fine-tuning an LLM on domain-specific data (legal, medical, code, support)
- Running QLoRA to fine-tune 70B models on consumer GPUs
- Setting up distributed training with DeepSpeed or FSDP
- Exporting fine-tuned adapters for production serving
- Implementing RLHF, DPO, or instruction tuning pipelines
## Prerequisites