Effortless Fine-Tuning of Large Language Models with Open-Source H2O LLM Studio
A framework and no-code GUI designed for fine-tuning state-of-the-art large language models (LLMs).
“Information flow is what the Internet is about. Information sharing is power. If you don’t share your ideas, smart people can’t do anything about them, and you’ll remain anonymous and powerless.” — Vint Cerf
While the pace at which Large Language Models (LLMs) have been driving breakthroughs is remarkable, these pre-trained models may not always be tailored to specific domains. Fine-tuning — the process of adapting a pre-trained language model to a specific task or domain—plays a critical role in NLP applications. However, fine-tuning can be challenging, requiring coding expertise and in-depth knowledge of model architecture and hyperparameters. Often, the underlying source code, weights, and architecture of popular LLMs are restricted by licensing or proprietary limitations, thereby limiting not only their customization but also the flexibility of these models, let alone the privacy and cost issues.
