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Average Ratings 0 Ratings

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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

Effortlessly switch between eager and graph modes using TorchScript, while accelerating your journey to production with TorchServe. The torch-distributed backend facilitates scalable distributed training and enhances performance optimization for both research and production environments. A comprehensive suite of tools and libraries enriches the PyTorch ecosystem, supporting development across fields like computer vision and natural language processing. Additionally, PyTorch is compatible with major cloud platforms, simplifying development processes and enabling seamless scaling. You can easily choose your preferences and execute the installation command. The stable version signifies the most recently tested and endorsed iteration of PyTorch, which is typically adequate for a broad range of users. For those seeking the cutting-edge, a preview is offered, featuring the latest nightly builds of version 1.10, although these may not be fully tested or supported. It is crucial to verify that you meet all prerequisites, such as having numpy installed, based on your selected package manager. Anaconda is highly recommended as the package manager of choice, as it effectively installs all necessary dependencies, ensuring a smooth installation experience for users. This comprehensive approach not only enhances productivity but also ensures a robust foundation for development.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Comet LLM Yes 
AWS Elastic Fabric Adapter (EFA) No 
Amazon EC2 P5 Instances No 
Apolo No 
Cameralyze No 
Cyfuture Cloud No 
Domino Enterprise AI Platform No 
ExecuTorch No 
Gemma 2 No 
Gemma 3 No 
Gemma 3n No 
Gemma 4 No 
Graphcore No 
LTXV No 
NVIDIA TensorRT No 
NodeShift No 
Sharon AI No 
Thunder Compute No 
Unify AI No 
vLLM No 

Integrations

Comet LLM Yes 
AWS Elastic Fabric Adapter (EFA) Yes 
Amazon EC2 P5 Instances Yes 
Apolo Yes 
Cameralyze Yes 
Cyfuture Cloud Yes 
Domino Enterprise AI Platform Yes 
ExecuTorch Yes 
Gemma 2 Yes 
Gemma 3 Yes 
Gemma 3n Yes 
Gemma 4 Yes 
Graphcore Yes 
LTXV Yes 
NVIDIA TensorRT Yes 
NodeShift Yes 
Sharon AI Yes 
Thunder Compute Yes 
Unify AI Yes 
vLLM Yes 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

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 Yes 
iPad App Yes 
Android App Yes 
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 Yes 
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

PyTorch

Founded

2016

Website

pytorch.org

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

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

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