Caffe

Caffe

BAIR
+

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About

Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license. Check out our web image classification demo! Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine then deploy to commodity clusters or mobile devices. Extensible code fosters active development. In Caffe’s first year, it has been forked by over 1,000 developers and had many significant changes contributed back. Thanks to these contributors the framework tracks the state-of-the-art in both code and models. Speed makes Caffe perfect for research experiments and industry deployment. Caffe can process over 60M images per day with a single NVIDIA K40 GPU.

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

Simple, fast, safe, and compiled. For developing maintainable software. Simple language for building maintainable programs. You can learn the entire language by going through the documentation over a weekend, and in most cases, there's only one way to do something. This results in simple, readable, and maintainable code. This results in simple, readable, and maintainable code. Despite being simple, V gives a lot of power to the developer and can be used in pretty much every field, including systems programming, webdev, gamedev, GUI, mobile, science, embedded, tooling, etc. V is very similar to Go. If you know Go, you already know 80% of V. Bounds checking, No undefined values, no variable shadowing, immutable variables by default, immutable structs by default, option/result and mandatory error checks, sum types, generics, and immutable function args by default, mutable args have to be marked on call.

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

Anyone looking for an open-source deep learning framework with expression, speed and modularity

Audience

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

Audience

Developers interested in a language for building maintainable programs

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

No information available.
Free Version
Free Trial

Pricing

Free
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

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

BAIR
United States
caffe.berkeleyvision.org

Company Information

PyTorch
Founded: 2016
pytorch.org

Company Information

V Programming Language
United States
vlang.io

Alternatives

DeepSpeed

DeepSpeed

Microsoft

Alternatives

Alternatives

MXNet

MXNet

The Apache Software Foundation
Core ML

Core ML

Apple
Swift

Swift

Apple
Vertex AI

Vertex AI

Google
Create ML

Create ML

Apple
MXNet

MXNet

The Apache Software Foundation
DeepSpeed

DeepSpeed

Microsoft
Zig

Zig

Zig Software Foundation

Categories

Categories

Categories

Deep Learning Features

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Integrations

Activeeon ProActive
Amazon EC2 Capacity Blocks for ML
Amazon SageMaker Studio Lab
CodeQwen
Collimator
Groq
IBM Distributed AI APIs
Intel Tiber AI Cloud
JFrog ML
JavaScript
Label Studio
Lightly
Modelbit
NVIDIA AI Foundations
NVIDIA Triton Inference Server
RunPod
Runyour AI
SiMa
Superwise
Zepl

Integrations

Activeeon ProActive
Amazon EC2 Capacity Blocks for ML
Amazon SageMaker Studio Lab
CodeQwen
Collimator
Groq
IBM Distributed AI APIs
Intel Tiber AI Cloud
JFrog ML
JavaScript
Label Studio
Lightly
Modelbit
NVIDIA AI Foundations
NVIDIA Triton Inference Server
RunPod
Runyour AI
SiMa
Superwise
Zepl

Integrations

Activeeon ProActive
Amazon EC2 Capacity Blocks for ML
Amazon SageMaker Studio Lab
CodeQwen
Collimator
Groq
IBM Distributed AI APIs
Intel Tiber AI Cloud
JFrog ML
JavaScript
Label Studio
Lightly
Modelbit
NVIDIA AI Foundations
NVIDIA Triton Inference Server
RunPod
Runyour AI
SiMa
Superwise
Zepl
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