Member-only story
Private GPT: Fine-Tune LLM on Enterprise Data
Doing cool things with data
Introduction
In the era of big data and advanced artificial intelligence, language models have emerged as formidable tools capable of processing and generating human-like text. Large Language Models like ChatGPT are general-purpose bots capable of having conversations on many topics. However, LLMs can also be fine-tuned on domain-specific data making them more accurate and on-point on domain-specific enterprise questions.
Many industries and applications will require a fine-tuned LLMs. Reasons include:
- Better performance from a chatbot trained on specific data
- OpenAI models like chatgpt are a black box and companies may be hesitant to share their confidential data over an API
- ChatGPT API costs may be prohibitive for large applications
The challenge with fine-tuning an LLM is that the process is unknown and the computational resources required to train a billion-parameter model without optimizations can be prohibitive.
Fortunately, a lot of research has been done on training techniques that allow us now to fine-tune LLMs on smaller GPUs.