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Description

The Gemma family consists of advanced, lightweight models developed using the same innovative research and technology as the Gemini models. These cutting-edge models are equipped with robust security features that promote responsible and trustworthy AI applications, achieved through carefully curated data sets and thorough refinements. Notably, Gemma models excel in their various sizes—2B, 7B, 9B, and 27B—often exceeding the performance of some larger open models. With the introduction of Keras 3.0, users can experience effortless integration with JAX, TensorFlow, and PyTorch, providing flexibility in framework selection based on specific tasks. Designed for peak performance and remarkable efficiency, Gemma 2 is specifically optimized for rapid inference across a range of hardware platforms. Furthermore, the Gemma family includes diverse models that cater to distinct use cases, ensuring they adapt effectively to user requirements. These lightweight language models feature a decoder and have been trained on an extensive array of textual data, programming code, and mathematical concepts, which enhances their versatility and utility in various applications.

Description

Transformers is a versatile library that includes pretrained models for natural language processing, computer vision, audio, and multimodal tasks, facilitating both inference and training. With the Transformers library, you can effectively train models tailored to your specific data, create inference applications, and utilize large language models for text generation. Visit the Hugging Face Hub now to discover a suitable model and leverage Transformers to kickstart your projects immediately. This library provides a streamlined and efficient inference class that caters to various machine learning tasks, including text generation, image segmentation, automatic speech recognition, and document question answering, among others. Additionally, it features a robust trainer that incorporates advanced capabilities like mixed precision, torch.compile, and FlashAttention, making it ideal for both training and distributed training of PyTorch models. The library ensures rapid text generation through large language models and vision-language models, and each model is constructed from three fundamental classes (configuration, model, and preprocessor), allowing for quick deployment in either inference or training scenarios. Overall, Transformers empowers users with the tools needed to create sophisticated machine learning solutions with ease and efficiency.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Hugging Face Yes 
PyTorch Yes 
AiAssistWorks Yes 
CSS Yes 
Database Mart Yes 
Elixir Yes 
F# Yes 
HTML Yes 
Java Yes 
JavaScript Yes 
Julia Yes 
Kaggle Yes 
Kotlin Yes 
LlamaCoder Yes 
Python Yes 
Ruby Yes 
Scala Yes 
TensorFlow Yes 
TypeScript Yes 
VESSL AI Yes 

Integrations

Hugging Face Yes 
PyTorch Yes 
AiAssistWorks No 
CSS No 
Database Mart No 
Elixir No 
F# No 
HTML No 
Java No 
JavaScript No 
Julia No 
Kaggle No 
Kotlin No 
LlamaCoder No 
Python No 
Ruby No 
Scala No 
TensorFlow No 
TypeScript No 
VESSL AI No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

$9 per month
Free Trial No 
Free Version Yes 

Deployment

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

Deployment

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

Customer Support

Business Hours No 
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 No 

Types of Training

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

Vendor Details

Company Name

Google

Country

United States

Website

ai.google.dev/gemma

Vendor Details

Company Name

Hugging Face

Founded

2016

Country

United States

Website

huggingface.co/docs/transformers/en/index

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