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Building Multimodal RAG Applications with Google Gemini

Text-to-Text Generation

Understand how to leverage Google Gemini's advanced text-to-text generation capabilities to automate proofreading, correct errors, translate content, and enhance text quality through practical implementation and prompt engineering.

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Text-to-text generation

Text-to-text generation is a process that involves processing some input text to generate some output text accordingly. The generated textual response depends on the nature of the input prompt. It can be a simple textual answer to a question or more advanced responses such as summarized text, translated text to any other language, information extracted from text, and so on.

Text generation is the basic functionality of most LLMs. Similarly, the Gemini model is designed to handle complex text generation tasks based on the provided instructions and data.

Text-to-text generation using Gemini
Text-to-text generation using Gemini

The best-suited Gemini models for text generation are gemini-1.0-pro, gemini-1.0-pro-001, gemini-1.0-pro-latest, gemini-1.5-pro-latest, and gemini-pro. ...