Cavalry 1 is a hello world model.
Whome to hello?
Run this model in Node.js with one line of code:
npm install replicate
REPLICATE_API_TOKEN
export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });
Run meltred/cavalry-1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "meltred/cavalry-1:fd1ca1dd118ad5d243a24cbb2ca9ff2bf87111f490ef33eb27a3d45ec92de97e", { input: { text: "World" } } ); console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
import replicate
output = replicate.run( "meltred/cavalry-1:fd1ca1dd118ad5d243a24cbb2ca9ff2bf87111f490ef33eb27a3d45ec92de97e", input={ "text": "World" } ) print(output)
To learn more, take a look at the guide on getting started with Python.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "meltred/cavalry-1:fd1ca1dd118ad5d243a24cbb2ca9ff2bf87111f490ef33eb27a3d45ec92de97e", "input": { "text": "World" } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
{ "completed_at": "2025-01-28T16:02:11.989278Z", "created_at": "2025-01-28T16:02:11.981000Z", "data_removed": false, "error": null, "id": "fcxy9drvhnrme0cmnpk889xfs8", "input": { "text": "World" }, "logs": null, "metrics": { "predict_time": 0.001184675, "total_time": 0.008278 }, "output": "Hello World!", "started_at": "2025-01-28T16:02:11.988093Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/fcxy9drvhnrme0cmnpk889xfs8", "cancel": "https://api.replicate.com/v1/predictions/fcxy9drvhnrme0cmnpk889xfs8/cancel" }, "version": "fd1ca1dd118ad5d243a24cbb2ca9ff2bf87111f490ef33eb27a3d45ec92de97e" }
This model runs on CPU hardware. We don't yet have enough runs of this model to provide performance information.
This model doesn't have a readme.
This model is cold. You'll get a fast response if the model is warm and already running, and a slower response if the model is cold and starting up.
This model runs on CPU hardware which costs $0.0001 per second. View more.