Machine learning doesn’t need to be so hard. Run models in the cloud at scale.

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Description

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

Push: You're building new products with machine learning. You don't have time to fight Python dependency hell, get mired in GPU configuration, or cobble together a Dockerfile. That's why we built Cog, an open-source tool that lets you package machine learning models in a standard, production-ready container.

Scale: Deploying machine learning models at scale is horrible. If you've tried, you know. API servers, weird dependencies, enormous model weights, CUDA, GPUs, batching. If you're building a product fast, you don't want to be dealing with this stuff. Replicate makes it easy to deploy machine learning models. You can use open-source models off the shelf, or you can deploy your own custom, private models at scale.

 

 

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Questions & Answers

How does Replicate work?

Replicate lets you run machine learning models with a cloud API, without having to understand the intricacies of machine learning or manage your own infrastructure. You can run open-source models that other people have published, or package and publish your own models. Those models can be public or private.

Nov. 6, 2023


How to run models in the browser?

You can run models on Replicate using the cloud API or the web.

The web interface is a good place to start when trying out a model for the first time. It gives you a visual view of all the inputs to the model, and generates a form for running the model right from your browser.

 

Nov. 6, 2023


How to run models with the API?

The web interface is great for getting acquainted with a model, but when you’re ready to integrate a model into something like a chat bot, website, or mobile app, that’s when the API comes into play.

Our HTTP API can be used with any programming language, but there are also client libraries for Python, JavaScript, and other languages that make it easier to use the API.

Using the Python client, you can create predictions with just a few lines of code:

Nov. 6, 2023