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 bring your own training data to create fine-tuned models, or build and publish custom models from scratch.
A model is a trained, packaged, and published software program that accepts inputs and returns outputs.
Whenever you run a model, you're creating a prediction. Learn about inputs, outputs, files, and other aspects of the prediction lifecycle.
Use deployments for more control over how your models run.
Webhooks provide real-time updates about your predictions.
Organizations let you share access to models, API tokens, billing, dashboards, and more.
Replicate is a pay-as-you-go platform. You are billed for the compute time used to run your models.
Build a Next.js web app that uses Replicate to run models and receive webhooks as they run.
Use Python to build and deploy a Discord chat bot application that uses Flux Schnell via Replicate to generate images from text prompts.
Learn how to build a SwiftUI app that uses Replicate to run a machine learning model.
Package your own custom model using Cog and push it to Replicate as a cloud API.
Learn how to push a Hugging Face Diffusers image generation model to Replicate as a scalable API.
Learn how to push a Hugging Face Transformers language model to Replicate.
Explore the differences between Flux Schnell and Flux Dev image generation models and learn how to enhance image quality effectively.
6 minutes
Here's a GPT-4-vision + ElevenLabs python script so you can star in your own Planet Earth.
2 minutes
Use language models like GPT-4o and Llama to write one-liner shell commands, then execute them.
4 minutes
Learn how to receive webhooks from Replicate's API when running predictions and trainings.
14 minutes