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Additional small spelling fixes for bq_dataframes_llm_output_schema.ipynb.
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notebooks/generative_ai/bq_dataframes_llm_output_schema.ipynb

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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"This notebook shows you how to create structured LLM output by specifying an outout schema when generating predictions with a Gemini model."
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"This notebook shows you how to create structured LLM output by specifying an output schema when generating predictions with a Gemini model."
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]
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"* Generative AI support on Vertex AI\n",
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"\n",
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"Learn about [BigQuery compute pricing](https://cloud.google.com/bigquery/pricing#analysis_pricing_models), [Generative AI support on Vertex AI pricing](https://cloud.google.com/vertex-ai/generative-ai/pricing),\n",
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"and [BigQuery ML pricing](https://cloud.google.com/bigquery/pricing#bqml),\n",
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"and [BigQuery ML pricing](https://cloud.google.com/bigquery/pricing#section-11),\n",
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"and use the [Pricing Calculator](https://cloud.google.com/products/calculator/)\n",
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"to generate a cost estimate based on your projected usage."
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"In the following example, the model output is formatted as integer valuesnto show the count of the city's rainy days:"
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"In the following example, the model output is formatted as integer values to show the count of the city's rainy days:"
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"metadata": {},
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"source": [
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"### Format output as multiple data types in one prediction\n",
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"You can generate multiple columns of output that use different data types in a single prediction. \n",
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"Within a single prediction, you can generate multiple columns of output that use different data types. \n",
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"\n",
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"The input doesn't have to bee dedicated prompts as long as the output column names are informative to the model."
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"The input doesn't have to be dedicated prompts as long as the output column names are informative to the model."
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