fine-tuning
Fine-tuning is the additional training of a pretrained AI model for a particular task or domain.
Fine-tuning is a technique that continues training an existing AI model on data for a particular task or domain. Unlike training a model from scratch, it adjusts parameters using a model that has already learned from data.
It differs from retrieval-augmented generation (RAG), which brings external information into a response without changing the model’s parameters.
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Articles covering this entry
…base reasoning through pre-training, the large-scale learning phase on vast data, while fine-tuning and post-training are bolted on afterward to shape behavior.
Prompting or fine-tuning a model to ask questions is not the same as giving it real mathematical uncertainty about what people value.
The Apache 2.0 license allows commercial use, modification and fine-tuning, which is the process of further training a model for a specific task, without licens…
Model training: Successful task runs supply examples for fine-tuning, while reinforcement learning tests and improves behavior through further attempts.