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Model Fine-Tuning

    When to Use Model Fine-tuning?
    When to Use Model Fine-tuning?
    Updated on 05 Nov 2025

    Model Fine-tuning is useful when:

    • You want the model to understand domain-specific knowledge (e.g., medical, legal, financial).

    • You want better performance on a specific task (e.g., translation, summarization, code generation).

    • You need the model to match a specific tone and style (e.g., formal writing, brand voice).

    • You need higher accuracy than prompt engineering or beddings can provide.

    But Model Fine-tuning is not needed when:

    • Your task can be solved with prompt engineering or one-shot/ few-shot examples.

    • You only need to filter/classify content (embedding models + classifiers may suffice).