Large Language Model (LLM) fine-tuning is adapting a pre-trained general-purpose language model (e.g., GPT, LLaMA, or BERT) to perform a specific task or align with domain-specific data.
While pre-trained LLMs possess extensive knowledge of language patterns, fine-tuning allows them to perform specialized applications, such as medical chatbots, legal document analysis, customer service agents, and more.
There are many methods for LLM fine-tuning, including prompt-tuning, full fine-tuning, and Parameter-Efficient Fine-Tuning (PEFT), but they will not be our focus.
In this article, I will outline five different LLM Fine-Tuning libraries that will certainly help your works.
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