Prediction

Model

sidhq/vzug:49e0e937

qrz7cc3bfyjqllqnf5iuhnlafq

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

17.8s

Created

about 2 years ago

Webhook

–

Input

prompt: In the style of TOK, a photo of a modern kitchen, white marble, large island
negative_prompt: Empty string
width: 1024
height: 1024
num_outputs: 1
scheduler: K_EULER
num_inference_steps: 50
guidance_scale: 7.5
prompt_strength: 0.8
refine: no_refiner
high_noise_frac: 0.8
apply_watermark: true
lora_scale: 0.6

{
  "apply_watermark": true,
  "guidance_scale": 7.5,
  "height": 1024,
  "high_noise_frac": 0.8,
  "lora_scale": 0.6,
  "negative_prompt": "",
  "num_inference_steps": 50,
  "num_outputs": 1,
  "prompt": "In the style of TOK, a photo of a modern kitchen, white marble, large island",
  "prompt_strength": 0.8,
  "refine": "no_refiner",
  "scheduler": "K_EULER",
  "width": 1024
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_Z5P**********************************

This is your API token. Keep it to yourself.

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 sidhq/vzug using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "sidhq/vzug:49e0e9370b5361ffd56e753209b065f8d0d55f754cd404784c1b136595f90911",
  {
    input: {
      apply_watermark: true,
      guidance_scale: 7.5,
      height: 1024,
      high_noise_frac: 0.8,
      lora_scale: 0.6,
      negative_prompt: "",
      num_inference_steps: 50,
      num_outputs: 1,
      prompt: "In the style of TOK, a photo of a modern kitchen, white marble, large island",
      prompt_strength: 0.8,
      refine: "no_refiner",
      scheduler: "K_EULER",
      width: 1024
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

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=r8_Z5P**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run sidhq/vzug using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "sidhq/vzug:49e0e9370b5361ffd56e753209b065f8d0d55f754cd404784c1b136595f90911",
    input={
        "apply_watermark": True,
        "guidance_scale": 7.5,
        "height": 1024,
        "high_noise_frac": 0.8,
        "lora_scale": 0.6,
        "negative_prompt": "",
        "num_inference_steps": 50,
        "num_outputs": 1,
        "prompt": "In the style of TOK, a photo of a modern kitchen, white marble, large island",
        "prompt_strength": 0.8,
        "refine": "no_refiner",
        "scheduler": "K_EULER",
        "width": 1024
    }
)

# To access the file URL:
print(output[0].url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output[0].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=r8_Z5P**********************************

This is your API token. Keep it to yourself.

Run sidhq/vzug 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": "sidhq/vzug:49e0e9370b5361ffd56e753209b065f8d0d55f754cd404784c1b136595f90911",
    "input": {
      "apply_watermark": true,
      "guidance_scale": 7.5,
      "height": 1024,
      "high_noise_frac": 0.8,
      "lora_scale": 0.6,
      "negative_prompt": "",
      "num_inference_steps": 50,
      "num_outputs": 1,
      "prompt": "In the style of TOK, a photo of a modern kitchen, white marble, large island",
      "prompt_strength": 0.8,
      "refine": "no_refiner",
      "scheduler": "K_EULER",
      "width": 1024
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

16.4 seconds

Tweak it Report