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About

​JAX is a Python library designed for high-performance numerical computing and machine learning research. It offers a NumPy-like API, facilitating seamless adoption for those familiar with NumPy. Key features of JAX include automatic differentiation, just-in-time compilation, vectorization, and parallelization, all optimized for execution on CPUs, GPUs, and TPUs. These capabilities enable efficient computation for complex mathematical functions and large-scale machine-learning models. JAX also integrates with various libraries within its ecosystem, such as Flax for neural networks and Optax for optimization tasks. Comprehensive documentation, including tutorials and user guides, is available to assist users in leveraging JAX's full potential. ​

About

Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe. Scalable distributed training and performance optimization in research and production is enabled by the torch-distributed backend. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling. Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, 1.10 builds that are generated nightly. Please ensure that you have met the prerequisites (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Professional researchers and developers searching for a solution to manage their numerical computing and machine learning operations in Python

Audience

Researchers in need of an open source machine learning solution to accelerate research prototyping and production deployment

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 5.0 / 5
ease 1.0 / 5
features 5.0 / 5
design 5.0 / 5
support 5.0 / 5

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

JAX
United States
docs.jax.dev/en/latest/

Company Information

PyTorch
Founded: 2016
pytorch.org

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Categories

Categories

Integrations

Flower
Gemma 3n
IREN Cloud
LiteRT
Amazon EC2 G5 Instances
Amazon EC2 Trn1 Instances
Amazon EC2 Trn2 Instances
Amazon EC2 UltraClusters
Amazon SageMaker Debugger
Daft
Equinox
Gemma 3
Giskard
Grain
HStreamDB
Hugging Face Transformers
MLReef
NVIDIA DeepStream SDK
NVIDIA Triton Inference Server
Vast.ai

Integrations

Flower
Gemma 3n
IREN Cloud
LiteRT
Amazon EC2 G5 Instances
Amazon EC2 Trn1 Instances
Amazon EC2 Trn2 Instances
Amazon EC2 UltraClusters
Amazon SageMaker Debugger
Daft
Equinox
Gemma 3
Giskard
Grain
HStreamDB
Hugging Face Transformers
MLReef
NVIDIA DeepStream SDK
NVIDIA Triton Inference Server
Vast.ai
Claim JAX and update features and information
Claim JAX and update features and information
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Claim PyTorch and update features and information