Head of AI at a consultancy with 1,001-5,000 employees
Real User
Top 10
Sep 29, 2025
To maximize the effectiveness of fine-tuning, I would suggest using the parallelism features of the platform. This allows fine-tuning and evaluating multiple models at the same time, making comparisons more informative and helping to choose the best configuration among a representative set of models.
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To maximize the effectiveness of fine-tuning, I would suggest using the parallelism features of the platform. This allows fine-tuning and evaluating multiple models at the same time, making comparisons more informative and helping to choose the best configuration among a representative set of models.
Evaluations can be costly.