Retrieve Axolotl Skill units from documentation for rapid discovery and activation.
npx skills add https://github.com/gigagiova/hermes-agent --skill axolotl-gigagiova
Please help me install this Agent Skill. Skill: axolotl Source: https://github.com/gigagiova/hermes-agent/tree/main/skills/mlops/axolotl Command: npx skills add https://github.com/gigagiova/hermes-agent --skill axolotl-gigagiova
Axolotl Skill documents and organizes the knowledge needed to implement and operate Axolotl training workflows, datasets, and RLHF setups, helping teams quickly onboard and execute end-to-end model training.
Review the API references and open the references/ directories to initialize your Axolotl training workflow.
High-intent search queries and answers about installing and using this skill.
Axolotl training workflows support supervised fine-tuning by providing documentation on model loading, data handling, and quick-start guidance to spin up a training pipeline. Review the API references and resource directories to initialize the configuration.
LoRA and QLoRA adapters are supported use cases within Axolotl training workflows. The documentation covers how to implement these adapters alongside pretraining, supervised fine-tuning, and reward modelling.
Configuring RLHF in Axolotl involves retrieving Skill units from documentation covering reward modelling and RLHF setups. It provides references and API docs to help teams execute end-to-end reinforcement learning workflows.
Axolotl documentation covers data handling and advanced optimizations for training workflows. It organizes knowledge on datasets and optimization techniques to help teams quickly onboard and execute model training.
Axolotl requires a SKILL.md frontmatter with name and description, optional resource directories, and a clearly defined entry point to load the skill into context. It focuses on documentation retrieval rather than executing training jobs directly.
Reviewing the references directory is required to initialize your Axolotl training workflow. It contains the API references and organized documentation needed to implement installation, data handling, and model loading procedures.
devMoezConfigure Axolotl YAML for LoRA/QLoRA fine-tuning and preference training.
OpenLAIRConfigure YAML-based Axolotl pipelines for LLM fine-tuning with RLHF and LoRA/QLoRA.
tachyon-beepRoute ML production concerns to relevant deployment, optimization, MLOps, and observability sub-skills.
nelohenriqDesign and execute LLM fine-tuning experiments with Axolotl YAML configs.
