Agent skill · research science · davila7
axolotl
Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support
Why this skill is useful
Adds executable scripts and detailed YAML configurations for fine-tuning LLMs with Axolotl that are not widely available in public documentation.
What it needs
Requires accelerate, axolotl, datasets, deepspeed, peft, torch, transformers installed locally. About 2k tokens when loaded. Last updated 2026-08-06. 30,138 stars on the source repository.
What this skill does
Axolotl Skill Comprehensive assistance with axolotl development, generated from official documentation. When to Use This Skill This skill should be triggered when: Working with axolotl Asking about axolotl features or APIs Implementing axolotl solutions Debugging axolotl code Learning axolotl best practices Quick Reference Common Patterns Pattern 1: To validate that acceptable data transfer speeds exist for your training job, running NCCL Tests can help pinpoint bottlenecks, for example: Pattern 2: Configure your model to use FSDP in the Axolotl yaml. For example: Pattern 3: The contextparallelsize should be a divisor of the total number of GPUs. For example: Pattern 4: For example: - With 8 GPUs and no sequence parallelism: 8 different batches processed per step - With 8 GPUs and contextparallelsize=4: Only 2 different batches processed per step (each split across 4 GPUs) - If your per-GPU microbatchsize is 2, the global batch size decreases from 16 to 4 Pattern 5: Setting savecompressed: true in your configuration enables saving models in a compressed format, which: - Reduces disk space usage by approximately 40% - Maintains compatibility with vLLM for accelerated inference - Maintains compatibility with llmcompressor for further optimization (example: quantization) Pattern 6: Note It is not necessary to place your integration in the integrations folder. It can be in any location, so long as it’s installed in a package in your python env. See this repo for an example: https://github.com/axolotl-ai-cloud/diff-transformer Pattern 7: Handle both single-example and batched data. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills davila7/fine-tuning-axolotl