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google-gemini / repository
This SDK is now deprecated, use the unified Firebase SDK.
With Gemini 2.0, we took the chance to create a unified SDK for mobile developers who want to use Google's GenAI models (Gemini, Veo, Imagen, etc). As part of that process, we took all of the feedback from this SDK and what developers like about other SDKs in the ecosystem to directly work with the Firebase SDK. We don't plan to add anything to this SDK or make any further changes. We know how disruptive an SDK change can be and don't take this change lightly, but our goal is to create an extremely simple and clear path for developers to build with our models so it felt necessary to make this change.
Thank you for building with Gemini and let us know if you need any help!
Do not use this repository. Use Firebase AI Logic instead.
Selected from shared topics, language and repository description—not editorial ratings.
NVIDIA /
NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.
aws /
This SDK has reached end-of-support. The AWS SDK for Go v2 is available here: https://github.com/aws/aws-sdk-go-v2
microsoft /
The C++ REST SDK is a Microsoft project for cloud-based client-server communication in native code using a modern asynchronous C++ API design. This project aims to help C++ developers connect to and interact with services.
Azure /
This repository is for active development of the Azure SDK for .NET. For consumers of the SDK we recommend visiting our public developer docs at https://learn.microsoft.com/dotnet/azure/ or our versioned developer docs at https://azure.github.io/azure-sdk-for-net.
Azure /
This repository is for active development of the Azure SDK for Python. For consumers of the SDK we recommend visiting our public developer docs at https://learn.microsoft.com/python/azure/ or our versioned developer docs at https://azure.github.io/azure-sdk-for-python.
py-why /
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.