|
- GitHub - google-deepmind gemma: Gemma open-weight LLM library, from . . .
Gemma is a family of open-weights Large Language Model (LLM) by Google DeepMind, based on Gemini research and technology This repository contains the implementation of the gemma PyPI package
- Gemma 3 model overview - Google AI for Developers
Gemma is a family of generative artificial intelligence (AI) models and you can use them in a wide variety of generation tasks, including question answering, summarization, and reasoning
- Gemma 3: Google’s new open model based on Gemini 2. 0
Gemma 3 outperforms other models in its size class, making it ideal for single-GPU or TPU applications Gemma 3 supports over 140 languages and offers advanced text and visual reasoning capabilities
- What is Gemma? Googles Open Sourced AI Model Explained
Gemma is a collection of lightweight open source generative AI (GenAI) models Gemma was created by the Google DeepMind research lab that also developed closed source Gemini, Google's generative AI chatbots
- Gemma: Open Models Based on Gemini Research and Technology
This work introduces Gemma, a family of lightweight, state-of-the art open models built from the research and technology used to create Gemini models Gemma models demonstrate strong performance across academic benchmarks for language understanding, reasoning, and safety
- Google Gemma 3 : Best Open-Weight AI Model Yet?
Explore Gemma 3 by Google: AI models designed for creative writing, multilingual tasks, and multimodal processing with unmatched performance
- Get started with Gemma models - Google AI for Developers
You can quickly test Gemma without setting up a development environment using Google AI Studio This web application lets you try out prompts with Gemma and evaluate its capabilities
- Welcome Gemma - Google’s new open LLM - Hugging Face
Gemma, a new family of state-of-the-art open LLMs, was released today by Google! It's great to see Google reinforcing its commitment to open-source AI, and we’re excited to fully support the launch with comprehensive integration in Hugging Face
|
|
|