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  1. Stackups
  2. AI
  3. Development & Training Tools
  4. Machine Learning Tools
  5. Carton vs Replicate

Carton vs Replicate

OverviewComparisonAlternatives

Overview

Replicate
Replicate
Stacks53
Followers12
Votes0
Carton
Carton
Stacks0
Followers1
Votes0
GitHub Stars425
Forks11

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Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

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CLI (Node.js)
or
Manual

Detailed Comparison

Replicate
Replicate
Carton
Carton

It lets you run machine learning models with a few lines of code, without needing to understand how machine learning works.

It is a library that lets you run any machine learning (ML) model from any programming language. It wraps existing models and provides a uniform interface for your application to use regardless of the framework the underlying model was implemented in.

Thousands of models, ready to use; Automatic API; Automatic scale; Pay by the second
One open-source API for all frameworks; Does not modify the original model, avoiding error-prone conversion steps
Statistics
GitHub Stars
-
GitHub Stars
425
GitHub Forks
-
GitHub Forks
11
Stacks
53
Stacks
0
Followers
12
Followers
1
Votes
0
Votes
0
Integrations
Python
Python
Cog
Cog
Next.js
Next.js
JavaScript
JavaScript
Vercel
Vercel
CUDA
CUDA
WebAssembly
WebAssembly
macOS
macOS
Linux
Linux

What are some alternatives to Replicate, Carton?

Git

Git

Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency.

TensorFlow

TensorFlow

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

Mercurial

Mercurial

Mercurial is dedicated to speed and efficiency with a sane user interface. It is written in Python. Mercurial's implementation and data structures are designed to be fast. You can generate diffs between revisions, or jump back in time within seconds.

scikit-learn

scikit-learn

scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.

PyTorch

PyTorch

PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.

SVN (Subversion)

SVN (Subversion)

Subversion exists to be universally recognized and adopted as an open-source, centralized version control system characterized by its reliability as a safe haven for valuable data; the simplicity of its model and usage; and its ability to support the needs of a wide variety of users and projects, from individuals to large-scale enterprise operations.

Keras

Keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/

NanoNets

NanoNets

Build a custom machine learning model without expertise or large amount of data. Just go to nanonets, upload images, wait for few minutes and integrate nanonets API to your application.

Kubeflow

Kubeflow

The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.

TensorFlow.js

TensorFlow.js

Use flexible and intuitive APIs to build and train models from scratch using the low-level JavaScript linear algebra library or the high-level layers API

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