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Stars
An open-source AI agent that brings the power of Gemini directly into your terminal.
Google Gen AI Python SDK provides an interface for developers to integrate Google's generative models into their Python applications.
An open protocol enabling communication and interoperability between opaque agentic applications.
An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.
Arena-Hard-Auto: An automatic LLM benchmark.
This repository compiles code samples and notebooks demonstrating how to use Generative AI on Google Cloud Vertex AI.
An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.
LLM Comparator is an interactive data visualization tool for evaluating and analyzing LLM responses side-by-side, developed by the PAIR team.
Open-source observability for your GenAI or LLM application, based on OpenTelemetry
Evaluation and Tracking for LLM Experiments and AI Agents
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI
A Python SDK for Vertex AI, a fully managed, end-to-end platform for data science and machine learning.
A framework for few-shot evaluation of language models.
Stable Diffusion web UI
Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.
Code for the paper "Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer"
Task-based datasets, preprocessing, and evaluation for sequence models.
Examples and guides for using the OpenAI API
A high-performance, zero-overhead, extensible Python compiler with built-in NumPy support
Model analysis tools for TensorFlow
Google Research
🤗 Evaluate: A library for easily evaluating machine learning models and datasets.
Models and examples built with TensorFlow
Notebooks, code samples, sample apps, and other resources that demonstrate how to use, develop and manage machine learning and generative AI workflows using Google Cloud Vertex AI.