Preeti
This tutorial provides a detailed guide on using the Gemini API Python SDK in Google Colab to access Google’s advanced large language models for tasks like text generation and multi-modal inputs. It emphasizes the convenience of Google Colab for running Python notebooks without additional environment configurations. Users without access to Google Colab can sign up for a free account. The tutorial covers the setup requirements for local environments, including Python 3.9+ and Jupyter for notebook execution.
To start using the Gemini API, users need to obtain an API key from Google AI Studio. The tutorial outlines the workflow for using Jupyter notebook in the browser using Google Colab, including installing the necessary packages, configuring the API key, and generating responses based on input prompts. It also demonstrates how to list available Gemini models for various tasks.
Overall, the tutorial highlights the integration of Google Colab with the Gemini API for advanced text generation tasks and provides a step-by-step guide for executing code in Google Colab. It showcases the capabilities of Google Colab for machine learning and data science projects by leveraging powerful computing resources without the need for local hardware and setup.
Source link
Source link: https://medium.com/@davidlfliang/intro-getting-started-with-gemini-api-using-google-colab-a2a9d01e9a9e?source=rss——ai-5
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