krunalmangroliya/uno-1:f572104d | Run with an API on Replicate

Version

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krunalmangroliya /uno-1:f572104d

Playground API

Input

prompt

*string

Shift + Return to add a new line

Text prompt for image generation.

image_ref1

file

Reference image 1 (optional).

image_ref2

file

Reference image 2 (optional).

image_ref3

file

Reference image 3 (optional).

image_ref4

file

Reference image 4 (optional).

width

integer

Width of the generated image.

Default: 1024

height

integer

Height of the generated image.

Default: 1024

num_steps

integer

(minimum: 1, maximum: 100)

Number of diffusion steps.

Default: 25

guidance

number

(minimum: 0)

Guidance scale. Higher values adhere more closely to the prompt.

Default: 4

seed

integer

Seed for random number generation. Use -1 for a random seed.

Default: -1

ref_size

integer

Reference image size for preprocessing. Use -1 for default (512 for 1 ref, 320 for multiple).

Default: -1

string

Positional encoding type.

Default: "d"

Run this model in Node.js with one line of code:

npx create-replicate --model=krunalmangroliya/uno-1

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run krunalmangroliya/uno-1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "krunalmangroliya/uno-1:f572104da40d522d3c6d95b2ac959cbb4eeede9c3f30be91d26c327ae1d1bd70",
  {
    input: {
      pe: "d",
      seed: -1,
      width: 1024,
      height: 1024,
      guidance: 4,
      ref_size: -1,
      num_steps: 25
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run krunalmangroliya/uno-1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "krunalmangroliya/uno-1:f572104da40d522d3c6d95b2ac959cbb4eeede9c3f30be91d26c327ae1d1bd70",
    input={
        "pe": "d",
        "seed": -1,
        "width": 1024,
        "height": 1024,
        "guidance": 4,
        "ref_size": -1,
        "num_steps": 25
    }
)

# To access the file URL:
print(output.url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output.read())

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run krunalmangroliya/uno-1 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "krunalmangroliya/uno-1:f572104da40d522d3c6d95b2ac959cbb4eeede9c3f30be91d26c327ae1d1bd70",
    "input": {
      "pe": "d",
      "seed": -1,
      "width": 1024,
      "height": 1024,
      "guidance": 4,
      "ref_size": -1,
      "num_steps": 25
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

No output yet! Press "Submit" to start a prediction.