Sample code and notebooks for Generative AI on Google Cloud, including Gemini
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Updated
May 6, 2024 - Jupyter Notebook
Sample code and notebooks for Generative AI on Google Cloud, including Gemini
The official notebooks are organized by Google Cloud Vertex AI products.
This repository contains notebooks for building knowledge graphs and using them to improve Retrieval Augmented Generation (RAG) systems. RAG leverages knowledge graphs with embedding models to enhance the quality of text retrieved for language models.
Contains a Jupyter Notebook that focuses on creating an AutoML trained model using Google Cloud Platform's Vertex AI to predict how long a customer will engage with a video ad for
This repository includes the Colab notebooks used for the AutoML benchmarking study (object detection), and some of the FiftyOne scripts used to generate the datasets.
This repository showcases the implementation of a chat model using Google Cloud's Vertex AI. The code is presented in a Jupyter Notebook environment and demonstrates how to set up, interact with, and customize a pre-trained chat model.
A collection of apps and projects that interact with Google Cloud APIs.
Public reusable components for Polyaxon
A GitHub Action for running a Google Cloud Vertex AI notebook.
This repository compiles code samples and notebooks demonstrating how to use Generative AI on Google Cloud Vertex AI.
Sample code and notebooks for Vertex AI, the end-to-end machine learning platform on Google Cloud
Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI
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