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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

JAX is a specialized Python library tailored for high-performance numerical computation and research in machine learning. It provides a familiar NumPy-like interface, making it easy for users already accustomed to NumPy to adopt it. Among its standout features are automatic differentiation, just-in-time compilation, vectorization, and parallelization, all of which are finely tuned for execution across CPUs, GPUs, and TPUs. These functionalities are designed to facilitate efficient calculations for intricate mathematical functions and expansive machine-learning models. Additionally, JAX seamlessly integrates with various components in its ecosystem, including Flax for building neural networks and Optax for handling optimization processes. Users can access extensive documentation, complete with tutorials and guides, to fully harness the capabilities of JAX. This wealth of resources ensures that both beginners and advanced users can maximize their productivity while working with this powerful library.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Python Yes 
AWS EC2 Trn3 Instances No 
Axolotl Yes 
Cake AI Yes 
Comet LLM Yes 
Equinox No 
Flower No 
Gemma 3n No 
Grain No 
Hugging Face No 
IREN Cloud No 
Keras No 
LiteRT No 
NumPy No 
Nurix Yes 
PyTorch Yes 
TensorFlow No 
Thunder Compute No 

Integrations

Python Yes 
AWS EC2 Trn3 Instances Yes 
Axolotl No 
Cake AI No 
Comet LLM No 
Equinox Yes 
Flower Yes 
Gemma 3n Yes 
Grain Yes 
Hugging Face Yes 
IREN Cloud Yes 
Keras Yes 
LiteRT Yes 
NumPy Yes 
Nurix No 
PyTorch No 
TensorFlow Yes 
Thunder Compute 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 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

JAX

Country

United States

Website

docs.jax.dev/en/latest/

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

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