In Murnitur, fine-tuning prompts is a way to customize and improve the performance of your AI models based on specific needs. You can fine-tune prompts using preset configurations or by applying reinforcement learning techniques with your completion datasets.
Murnitur provides preset configurations that can be fine-tuned to better fit your requirements. For example, you can load a preset designed for Question and Answer tasks and then fine-tune for better output:
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preset = murnitur.load_preset("QA")prompts = preset.fine_tune() # Fine-tunes the preset with the current active version
If you want to use a specific version of the preset, you can pass the version as an argument.
For more advanced customization, you can use completion datasets to fine-tune prompts. This approach is similar to reinforcement learning, where the model is trained based on specific data to improve its responses:
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prompts = preset.fine_tune_with_dataset('DATASET-ID') # Fine-tunes the preset with a dataset
Replace 'DATASET-ID' with the identifier of your dataset. You can also pass a specific prompt version if needed.