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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.

About

Unlambda is a programming language. Nothing remarkable there. The originality of Unlambda is that it stands as the unexpected intersection of two marginal families of languages. Functional programming languages, of which the canonical representative is Scheme (a Lisp dialect). This means that the basic object manipulated by the language (and indeed the only one as far as Unlambda is concerned) is the function. Rather, Unlambda uses a functional approach to programming: the only form of objects it manipulates are functions. Each function takes a function as an argument and returns a function. Apart from a binary “apply” operation, Unlambda provides several built-in functions (the most important ones being the K and S combinators). User-defined functions can be created, but not saved or named, because Unlambda does not have any variables.

About

WebAssembly (abbreviated Wasm) is a binary instruction format for a stack-based virtual machine. Wasm is designed as a portable compilation target for programming languages, enabling deployment on the web for client and server applications. The Wasm stack machine is designed to be encoded in a size- and load-time-efficient binary format. WebAssembly aims to execute at native speed by taking advantage of common hardware capabilities available on a wide range of platforms. WebAssembly describes a memory-safe, sandboxed execution environment that may even be implemented inside existing JavaScript virtual machines. When embedded in the web, WebAssembly will enforce the same-origin and permissions security policies of the browser. WebAssembly is designed to be pretty-printed in a textual format for debugging, testing, experimenting, optimizing, learning, teaching, and writing programs by hand. The textual format will be used when viewing the source of Wasm modules on the web.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

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

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

Audience

Developers in need of an advanced Programming Language solution

Audience

Developers

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

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

Reviews/Ratings

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

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

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

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

PyTorch
Founded: 2016
pytorch.org

Company Information

Unlambda
www.madore.org/~david/programs/unlambda/

Company Information

WebAssembly
Founded: 2015
webassembly.org

Alternatives

Alternatives

Alternatives

AssemblyScript

AssemblyScript

The AssemblyScript Project
Core ML

Core ML

Apple
Racket

Racket

Racket Language
Modsurfer

Modsurfer

Dylibso
Create ML

Create ML

Apple
DeepSpeed

DeepSpeed

Microsoft
AWS Neuron

AWS Neuron

Amazon Web Services
Zig

Zig

Zig Software Foundation

Categories

Categories

Categories

Integrations

AWS Elastic Fabric Adapter (EFA)
Amazon S3 Express One Zone
Amazon SageMaker Model Building
Amazon Web Services (AWS)
Fuzzball
Gemma 3
Humtap
Label Studio
Lightly
Lightning AI
MegaETH
NeevCloud
PostgresML
SuperDuperDB
Unify AI
Zed
Zellij
io.net
spaCy
voyage-3-large

Integrations

AWS Elastic Fabric Adapter (EFA)
Amazon S3 Express One Zone
Amazon SageMaker Model Building
Amazon Web Services (AWS)
Fuzzball
Gemma 3
Humtap
Label Studio
Lightly
Lightning AI
MegaETH
NeevCloud
PostgresML
SuperDuperDB
Unify AI
Zed
Zellij
io.net
spaCy
voyage-3-large

Integrations

AWS Elastic Fabric Adapter (EFA)
Amazon S3 Express One Zone
Amazon SageMaker Model Building
Amazon Web Services (AWS)
Fuzzball
Gemma 3
Humtap
Label Studio
Lightly
Lightning AI
MegaETH
NeevCloud
PostgresML
SuperDuperDB
Unify AI
Zed
Zellij
io.net
spaCy
voyage-3-large
Claim PyTorch and update features and information
Claim PyTorch and update features and information
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