finetune-train

What problem does it solve?

This Skill streamlines the process of training a fine-tuned language model and rigorously evaluating its performance improvements against a base model, ensuring a robust and effective outcome.

Core Features & Use Cases

• Supervised Fine-Tuning (SFT): Guides the model through a supervised training process using prepared datasets.
• GGUF Conversion & Upload: Converts the trained model into the GGUF format for local deployment and uploads it to HuggingFace Hub.
• Rigorous Evaluation: Compares the fine-tuned model against the base model using statistical methods to confirm significant improvements.
• Use Case: After preparing a dataset of therapeutic conversations, use this Skill to fine-tune a base LLM, convert it to a locally runnable GGUF format, and then confirm through evaluation that it outperforms the original model in therapeutic coaching quality.

Quick Start

Use the finetune-train skill to train a model using your prepared training data and evaluate its performance.