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Average Ratings 0 Ratings

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ease
features
design
support

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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

The Qualcomm Cloud AI SDK serves as a robust software suite aimed at enhancing the performance of trained deep learning models for efficient inference on Qualcomm Cloud AI 100 accelerators. It accommodates a diverse array of AI frameworks like TensorFlow, PyTorch, and ONNX, which empowers developers to compile, optimize, and execute models with ease. Offering tools for onboarding, fine-tuning, and deploying models, the SDK streamlines the entire process from preparation to production rollout. In addition, it includes valuable resources such as model recipes, tutorials, and sample code to support developers in speeding up their AI projects. This ensures a seamless integration with existing infrastructures, promoting scalable and efficient AI inference solutions within cloud settings. By utilizing the Cloud AI SDK, developers are positioned to significantly boost the performance and effectiveness of their AI-driven applications, ultimately leading to more innovative solutions in the field.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Hugging Face
PyTorch
TensorFlow
AiAssistWorks
Amazon Web Services (AWS)
Cirrascale
Database Mart
Docker
EndoAim
GIGABYTE Rack Server
Google AI Studio
HPE Apollo
Julia
LM-Kit.NET
LangChain
Nebius Token Factory
R
Rust
SQL
VESSL AI

Integrations

Hugging Face
PyTorch
TensorFlow
AiAssistWorks
Amazon Web Services (AWS)
Cirrascale
Database Mart
Docker
EndoAim
GIGABYTE Rack Server
Google AI Studio
HPE Apollo
Julia
LM-Kit.NET
LangChain
Nebius Token Factory
R
Rust
SQL
VESSL AI

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Google

Country

United States

Website

ai.google.dev/gemma

Vendor Details

Company Name

Qualcomm

Website

www.qualcomm.com/developer/software/cloud-ai-sdk

Product Features

Product Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Alternatives

Alternatives

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