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### Fine tuning
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Fine tuning a model on training data can both improve the results (by giving the model more examples to learn from) and reduce the cost & latency of API calls (by reducing the need to include training examples in prompts).
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Fine tuning a model on training data can both improve the results (by giving the model more examples to learn from) and reduce the cost/latency of API calls (chiefly through reducing the need to include training examples in prompts).
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Examples of fine tuning are shared in the following Jupyter notebooks:
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- Python 3.7.1+
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In general we want to support the versions of Python that our
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customers are using, so if you run into issues with any version
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In general, we want to support the versions of Python that our
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customers are using. If you run into problems with any version
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