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Description

DataGemma signifies a groundbreaking initiative by Google aimed at improving the precision and dependability of large language models when handling statistical information. Released as a collection of open models, DataGemma utilizes Google's Data Commons, a comprehensive source of publicly available statistical information, to root its outputs in actual data. This project introduces two cutting-edge methods: Retrieval Interleaved Generation (RIG) and Retrieval Augmented Generation (RAG). The RIG approach incorporates real-time data verification during the content generation phase to maintain factual integrity, while RAG focuses on acquiring pertinent information ahead of producing responses, thereby minimizing the risk of inaccuracies often referred to as AI hallucinations. Through these strategies, DataGemma aspires to offer users more reliable and factually accurate answers, representing a notable advancement in the effort to combat misinformation in AI-driven content. Ultimately, this initiative not only underscores Google's commitment to responsible AI but also enhances the overall user experience by fostering trust in the information provided.

Description

Gemma represents a collection of cutting-edge, lightweight open models that are built upon the same research and technology underlying the Gemini models. Created by Google DeepMind alongside various teams at Google, the inspiration for Gemma comes from the Latin word "gemma," which translates to "precious stone." In addition to providing our model weights, we are also offering tools aimed at promoting developer creativity, encouraging collaboration, and ensuring the ethical application of Gemma models. Sharing key technical and infrastructural elements with Gemini, which stands as our most advanced AI model currently accessible, Gemma 2B and 7B excel in performance within their weight categories when compared to other open models. Furthermore, these models can conveniently operate on a developer's laptop or desktop, demonstrating their versatility. Impressively, Gemma not only outperforms significantly larger models on crucial benchmarks but also maintains our strict criteria for delivering safe and responsible outputs, making it a valuable asset for developers.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Axolotl No 
C++ No 
Clojure No 
GaiaNet No 
Gemini Yes 
Gemini Enterprise Agent Platform No 
Gemini Nano Yes 
Google AI Studio No 
Jan No 
Java No 
Julia No 
Kerlig No 
Locally AI No 
Pioneer No 
Python No 
Rust No 
TensorFlow No 
TranslateGemma No 
TypeScript No 
Undrstnd No 

Integrations

Axolotl Yes 
C++ Yes 
Clojure Yes 
GaiaNet Yes 
Gemini No 
Gemini Enterprise Agent Platform Yes 
Gemini Nano No 
Google AI Studio Yes 
Jan Yes 
Java Yes 
Julia Yes 
Kerlig Yes 
Locally AI Yes 
Pioneer Yes 
Python Yes 
Rust Yes 
TensorFlow Yes 
TranslateGemma Yes 
TypeScript Yes 
Undrstnd Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based No 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Google

Founded

1994

Country

United States

Website

blog.google/technology/ai/google-datagemma-ai-llm/

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

ai.google.dev/gemma

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