Fine Tuning Insights
Fine tuning models can significantly enhance performance, especially for smaller, specialized tasks. However, it comes with challenges, including the need for continuous evaluation and adaptation as products evolve. The cost implications can be substantial, particularly for general-purpose applications that require frequent updates. Narrow use cases can help mitigate these expenses, making stability a key factor in the fine-tuning process.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Building Real-World LLM Products with Fine-Tuning and More with Hamel Husain - 694
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