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Implementing LLMs with LitGPT

A skill that walks you through loading, fine-tuning (LoRA/QLoRA), pretraining and deploying 20+ LLM architectures with Lightning AI's LitGPT.

Dev & CodingAdvanced★ 11,726⑂ 856AI score 8/10Last updated: Jun 16, 2026

What it does

  • Covers LitGPT installation and loading 20+ pretrained models (Phi-2, Llama 3, Gemma, Qwen, Mistral) via LLM.load().
  • Provides checklist workflows: prepare an Alpaca-style JSON dataset → full or LoRA fine-tune → merge adapters.
  • Explains pretraining from scratch on domain corpora with FSDP, multi-GPU and SLURM launches.
  • Includes deployment steps — quantization, GGUF conversion, FastAPI serving — plus fixes for OOM and slow training.
  • Compares LitGPT with Axolotl/TRL, Megatron-Core and vLLM so you know when to pick it.

Who it's for

  • ML engineers fine-tuning small LLMs on a single 12–16GB GPU.
  • Researchers and students who want single-file, abstraction-free architecture code to learn from.
  • Teams already in the Lightning ecosystem or pretraining domain-specific models.

Examples

  1. "LoRA fine-tune Phi-2 on 3,000 support tickets" → dataset formatting, litgpt finetune_lora flags, memory estimates.
  2. "I hit OOM full fine-tuning a 7B model" → switch to LoRA, tune micro/global batch size, enable gradient accumulation.
  3. "Serve my trained adapter behind an API" → merge_lora, quantize, then a FastAPI endpoint snippet.

· · · Install guide · · ·

Try it now, no install

Paste this into Claude to use the skill without installing anything.

Read the instructions in this file and follow them to help me:
https://raw.githubusercontent.com/Orchestra-Research/AI-Research-SKILLs/HEAD/01-model-architecture/litgpt/SKILL.md

What I want: (describe your task here)

If Claude can't open the link, open it yourself and paste the contents instead.

↓ If it works for you, download the ZIP below and install it. Then it runs on its own — no pasting each time.

Install in the Claude app (no terminal)
  1. Download the ZIP with the button below.
  2. In Claude, open Settings → Capabilities and turn on 'Code execution and file creation'. (one time)
  3. Go to Customize → Skills → + → 'Upload a skill' and upload the ZIP.
↓ Download ZIP
Install in Claude Code

Let Claude do it — paste this into Claude Code

Install the skill I found on Claude Skill Mart.
Copy the 01-model-architecture/litgpt folder from the GitHub repo Orchestra-Research/AI-Research-SKILLs into my ~/.claude/skills/implementing-llms-litgpt/.
When it's done, tell me in one line what this skill can do.

Install with a command instead

git clone https://github.com/Orchestra-Research/AI-Research-SKILLs.git && mkdir -p ~/.claude/skills && cp -r AI-Research-SKILLs/01-model-architecture/litgpt ~/.claude/skills/implementing-llms-litgpt

⚠ This is a third-party skill. Check the source repository before installing.

  1. Open a terminal and make sure Claude Code is installed.
  2. Clone the skill repository: git clone https://github.com/Orchestra-Research/AI-Research-SKILLs.git
  3. Create the skills folder: mkdir -p ~/.claude/skills
  4. Copy just this skill: cp -r AI-Research-SKILLs/01-model-architecture/litgpt ~/.claude/skills/implementing-llms-litgpt
  5. To actually run training, install the library: pip install 'litgpt[extra]' (an NVIDIA/CUDA GPU is recommended).
  6. Restart Claude Code and try a prompt like "Help me LoRA fine-tune Phi-2 with LitGPT."
View source on GitHub ↗License: MIT