gpt-llm-trainer

gpt-llm-trainer is an experimental notebook pipeline for creating task-specific fine-tuned language models from a plain task description. It reduces the work normally required to collect examples, format a dataset, split training and validation data, and run fine-tuning code. The system can generate prompts and responses with larger models, then prepare that synthetic dataset for model training. It includes workflows for LLaMA 2 7B, GPT-3.5 fine-tuning, and a Claude-to-LLaMA training variant. The project is designed for fast experimentation rather than polished enterprise model operations. It is useful for builders who want to test whether a narrowly focused model can be trained from generated examples.