Fine-tuning is just one step in the LLM journey. As mentioned in the #DATEV example, fine-tuning was crucial for data anonymization, a necessary pre-phase for analyzing and gaining insights from customer feedback in a way that is compliant with GDPR. Dr. Jonas Rende and Mareike Hoffmann Hoffman's #QED video provides a fascinating look at this process. 📽 https://lnkd.in/dirhgjFx 🤯 Note: While fine-tuning can tailor a model to a specific task, it can also make it less versatile. This specialization can limit its effectiveness in broader contexts. #finetuning #LLM #pragmaticAI #anonymization
Giulia Solinas, Ph.D.’s Post
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