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What is Gemma 2?
The Gemma family is composed of advanced and lightweight models that are built upon the same groundbreaking research and technology as the Gemini line. These state-of-the-art models come with powerful security features that foster responsible and trustworthy AI usage, a result of meticulously selected data sets and comprehensive refinements. Remarkably, the Gemma models perform exceptionally well in their varied sizes—2B, 7B, 9B, and 27B—frequently surpassing the capabilities of some larger open models. With the launch of Keras 3.0, users benefit from seamless integration with JAX, TensorFlow, and PyTorch, allowing for adaptable framework choices tailored to specific tasks. Optimized for peak performance and exceptional efficiency, Gemma 2 in particular is designed for swift inference on a wide range of hardware platforms. Moreover, the Gemma family encompasses a variety of models tailored to meet different use cases, ensuring effective adaptation to user needs. These lightweight language models are equipped with a decoder and have undergone training on a broad spectrum of textual data, programming code, and mathematical concepts, which significantly boosts their versatility and utility across numerous applications. This diverse approach not only enhances their performance but also positions them as a valuable resource for developers and researchers alike.
What is ERNIE 3.0 Titan?
Pre-trained language models have advanced significantly, demonstrating exceptional performance in various Natural Language Processing (NLP) tasks. The remarkable features of GPT-3 illustrate that scaling these models can lead to the discovery of their immense capabilities. Recently, the introduction of a comprehensive framework called ERNIE 3.0 has allowed for the pre-training of large-scale models infused with knowledge, resulting in a model with an impressive 10 billion parameters. This version of ERNIE 3.0 has outperformed many leading models across numerous NLP challenges. In our pursuit of exploring the impact of scaling, we have created an even larger model named ERNIE 3.0 Titan, which boasts up to 260 billion parameters and is developed on the PaddlePaddle framework. Moreover, we have incorporated a self-supervised adversarial loss coupled with a controllable language modeling loss, which empowers ERNIE 3.0 Titan to generate text that is both accurate and adaptable, thus extending the limits of what these models can achieve. This innovative methodology not only improves the model's overall performance but also paves the way for new research opportunities in the fields of text generation and fine-tuning control. As the landscape of NLP continues to evolve, the advancements in these models promise to drive further breakthroughs in understanding and generating human language.
Integrations Supported
C#
C++
CSS
Clojure
Database Mart
ERNIE Bot
Gemma
Google AI Studio
Google Cloud Platform
Google Colab
Integrations Supported
C#
C++
CSS
Clojure
Database Mart
ERNIE Bot
Gemma
Google AI Studio
Google Cloud Platform
Google Colab
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Company Location
United States
Company Website
ai.google.dev/gemma
Company Facts
Organization Name
Baidu
Date Founded
2000
Company Location
China
Company Website
research.baidu.com/Public/uploads/61c4362c79ee8.pdf