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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

DeepSpeed is an open-source library focused on optimizing deep learning processes for PyTorch. Its primary goal is to enhance efficiency by minimizing computational power and memory requirements while facilitating the training of large-scale distributed models with improved parallel processing capabilities on available hardware. By leveraging advanced techniques, DeepSpeed achieves low latency and high throughput during model training. This tool can handle deep learning models with parameter counts exceeding one hundred billion on contemporary GPU clusters, and it is capable of training models with up to 13 billion parameters on a single graphics processing unit. Developed by Microsoft, DeepSpeed is specifically tailored to support distributed training for extensive models, and it is constructed upon the PyTorch framework, which excels in data parallelism. Additionally, the library continuously evolves to incorporate cutting-edge advancements in deep learning, ensuring it remains at the forefront of AI technology.

Description

The Intel® Distribution of OpenVINO™ toolkit serves as an open-source AI development resource that speeds up inference on various Intel hardware platforms. This toolkit is crafted to enhance AI workflows, enabling developers to implement refined deep learning models tailored for applications in computer vision, generative AI, and large language models (LLMs). Equipped with integrated model optimization tools, it guarantees elevated throughput and minimal latency while decreasing the model size without sacrificing accuracy. OpenVINO™ is an ideal choice for developers aiming to implement AI solutions in diverse settings, spanning from edge devices to cloud infrastructures, thereby assuring both scalability and peak performance across Intel architectures. Ultimately, its versatile design supports a wide range of AI applications, making it a valuable asset in modern AI development.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

PyTorch Yes 
Axolotl Yes 
Caffe No 
Cake AI Yes 
Cameralyze No 
Comet LLM Yes 
EndoAim No 
Hugging Face No 
Intel Geti No 
Intel Open Edge Platform No 
Keras No 
LaunchX No 
Nero AI No 
Nurix Yes 
Nutanix Karbon Platform Services No 
ONNX No 
PaddlePaddle No 
Python Yes 
TensorFlow No 

Integrations

PyTorch Yes 
Axolotl No 
Caffe Yes 
Cake AI No 
Cameralyze Yes 
Comet LLM No 
EndoAim Yes 
Hugging Face Yes 
Intel Geti Yes 
Intel Open Edge Platform Yes 
Keras Yes 
LaunchX Yes 
Nero AI Yes 
Nurix No 
Nutanix Karbon Platform Services Yes 
ONNX Yes 
PaddlePaddle Yes 
Python No 
TensorFlow Yes 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
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 No 

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

Microsoft

Founded

1975

Country

United States

Website

www.deepspeed.ai/

Vendor Details

Company Name

Intel

Founded

1968

Country

United States

Website

www.intel.com/content/www/us/en/developer/tools/openvino-toolkit/overview.html

Product Features

Deep Learning

Convolutional Neural Networks No 
Document Classification No 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization No 

Product Features

Deep Learning

Convolutional Neural Networks No 
Document Classification No 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization No 

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