Fine-tune Large Language Models with Axolotl using YAML configurations.
npx skills add https://github.com/hhhi21g/HealthCenter --skill axolotl-hhhi21g
Please help me install this Agent Skill. Skill: axolotl Source: https://github.com/hhhi21g/HealthCenter/tree/main/.codex/skills/axolotl Command: npx skills add https://github.com/hhhi21g/HealthCenter --skill axolotl-hhhi21g
This Skill provides expert guidance and tools for fine-tuning Large Language Models (LLMs) with Axolotl, enabling efficient and effective model adaptation for specific tasks.
Run the skill with the following command: axolotl --config ./fine_tuning_config.yaml
High-intent search queries and answers about installing and using this skill.
To fine-tune an LLM for specific tasks, you can use YAML configuration templates to define training and evaluation settings, then execute the run with `axolotl --config ./fine_tuning_config.yaml`. This provides guidance for text generation, question answering, and summarization.
The best way to configure model training is by using YAML configuration templates that adjust various training settings and evaluation metrics. This allows efficient adaptation of large language models for specific downstream tasks.
Yes, you need DeepSpeed and PEFT, along with torch, transformers, datasets, and accelerate. These dependencies are required to execute the model training and fine-tuning processes efficiently.
Yes, you can use this fine-tuning method for question answering, text generation, and summarization. It provides comprehensive instructions and examples to adapt large language models for these specific use cases.
Your fine-tuning configuration may fail if required dependencies like axolotl, torch, or transformers are missing, or if the YAML configuration file is incorrectly structured. Ensure all deep learning libraries are installed and paths are correct.
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