Fine Tuning Large Language Models (LLMs) with Domain Specific Datasets
Large language models (LLMs) are trained on massive, publicly available text datasets containing trillions of tokens. However, these models do not necessarily possess sufficient subject matter expertise and often struggle to provide meaningful responses to specialized prompts. Therefore, fine-tuning LLMs with domain-specific datasets – extracted from documents, articles, and other sources – is crucial. In this presentation, we will demonstrate fine-tuning a few smaller LLMs with LoRA approach using instruct datasets on Gaudi hardware.
Remote event