Prediction

ID

i3fnuutbl3twsqtkajwplspr5a

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

41.6s

Created

over 1 year ago

Input

width: 1152
height: 768
prompt: A TOK red shopping aisle
refine: expert_ensemble_refiner
scheduler: K_EULER
lora_scale: 0.6
num_outputs: 4
guidance_scale: 7.5
apply_watermark
high_noise_frac: 0.8
negative_prompt
prompt_strength: 0.8
num_inference_steps: 50

{
  "width": 1152,
  "height": 768,
  "prompt": "A TOK red shopping aisle",
  "refine": "expert_ensemble_refiner",
  "scheduler": "K_EULER",
  "lora_scale": 0.6,
  "num_outputs": 4,
  "guidance_scale": 7.5,
  "apply_watermark": false,
  "high_noise_frac": 0.8,
  "negative_prompt": "",
  "prompt_strength": 0.8,
  "num_inference_steps": 50
}

npm install replicate

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 fofr/sdxl-color using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/sdxl-color:454561fe18009840dd04e07df5012cdad42b8dfe87e6814c9f8e3e323d9bcfbe",
  {
    input: {
      width: 1152,
      height: 768,
      prompt: "A TOK red shopping aisle",
      refine: "expert_ensemble_refiner",
      scheduler: "K_EULER",
      lora_scale: 0.6,
      num_outputs: 4,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.8,
      negative_prompt: "",
      prompt_strength: 0.8,
      num_inference_steps: 50
    }
  }
);

// 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.

fofr/sdxl-color:454561fe18009840dd04e07df5012cdad42b8dfe87e6814c9f8e3e323d9bcfbe

pip install replicate

Import the client:

import replicate

Run fofr/sdxl-color using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/sdxl-color:454561fe18009840dd04e07df5012cdad42b8dfe87e6814c9f8e3e323d9bcfbe",
    input={
        "width": 1152,
        "height": 768,
        "prompt": "A TOK red shopping aisle",
        "refine": "expert_ensemble_refiner",
        "scheduler": "K_EULER",
        "lora_scale": 0.6,
        "num_outputs": 4,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.8,
        "negative_prompt": "",
        "prompt_strength": 0.8,
        "num_inference_steps": 50
    }
)
print(output)

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

Run fofr/sdxl-color 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": "fofr/sdxl-color:454561fe18009840dd04e07df5012cdad42b8dfe87e6814c9f8e3e323d9bcfbe",
    "input": {
      "width": 1152,
      "height": 768,
      "prompt": "A TOK red shopping aisle",
      "refine": "expert_ensemble_refiner",
      "scheduler": "K_EULER",
      "lora_scale": 0.6,
      "num_outputs": 4,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.8,
      "negative_prompt": "",
      "prompt_strength": 0.8,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

39.8 seconds

Tweak it Share Report

Prediction

Model

ID

7i4onwlb6dl5sq4nn4qux5heiq

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

40.7s

Created

over 1 year ago

Input

width: 1152
height: 768
prompt: A TOK blue room
refine: expert_ensemble_refiner
scheduler: K_EULER
lora_scale: 0.6
num_outputs: 4
guidance_scale: 7.5
apply_watermark
high_noise_frac: 0.8
negative_prompt
prompt_strength: 0.8
num_inference_steps: 50

{
  "width": 1152,
  "height": 768,
  "prompt": "A TOK blue room",
  "refine": "expert_ensemble_refiner",
  "scheduler": "K_EULER",
  "lora_scale": 0.6,
  "num_outputs": 4,
  "guidance_scale": 7.5,
  "apply_watermark": false,
  "high_noise_frac": 0.8,
  "negative_prompt": "",
  "prompt_strength": 0.8,
  "num_inference_steps": 50
}

npm install replicate

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 fofr/sdxl-color using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/sdxl-color:454561fe18009840dd04e07df5012cdad42b8dfe87e6814c9f8e3e323d9bcfbe",
  {
    input: {
      width: 1152,
      height: 768,
      prompt: "A TOK blue room",
      refine: "expert_ensemble_refiner",
      scheduler: "K_EULER",
      lora_scale: 0.6,
      num_outputs: 4,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.8,
      negative_prompt: "",
      prompt_strength: 0.8,
      num_inference_steps: 50
    }
  }
);

// 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.

fofr/sdxl-color:454561fe18009840dd04e07df5012cdad42b8dfe87e6814c9f8e3e323d9bcfbe

pip install replicate

Import the client:

import replicate

Run fofr/sdxl-color using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/sdxl-color:454561fe18009840dd04e07df5012cdad42b8dfe87e6814c9f8e3e323d9bcfbe",
    input={
        "width": 1152,
        "height": 768,
        "prompt": "A TOK blue room",
        "refine": "expert_ensemble_refiner",
        "scheduler": "K_EULER",
        "lora_scale": 0.6,
        "num_outputs": 4,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.8,
        "negative_prompt": "",
        "prompt_strength": 0.8,
        "num_inference_steps": 50
    }
)
print(output)

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

Run fofr/sdxl-color 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": "fofr/sdxl-color:454561fe18009840dd04e07df5012cdad42b8dfe87e6814c9f8e3e323d9bcfbe",
    "input": {
      "width": 1152,
      "height": 768,
      "prompt": "A TOK blue room",
      "refine": "expert_ensemble_refiner",
      "scheduler": "K_EULER",
      "lora_scale": 0.6,
      "num_outputs": 4,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.8,
      "negative_prompt": "",
      "prompt_strength": 0.8,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

39.9 seconds

Tweak it Share Report

Prediction

Model

ID

35nvo6dbr36yhl6b6lapd2zrhy

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

48.6s

Created

over 1 year ago

Input

width: 1024
height: 1024
prompt: A TOK red living room, sofa
refine: expert_ensemble_refiner
scheduler: K_EULER
lora_scale: 0.6
num_outputs: 4
guidance_scale: 7.5
apply_watermark
high_noise_frac: 0.8
negative_prompt
prompt_strength: 0.8
num_inference_steps: 50

{
  "width": 1024,
  "height": 1024,
  "prompt": "A TOK red living room, sofa",
  "refine": "expert_ensemble_refiner",
  "scheduler": "K_EULER",
  "lora_scale": 0.6,
  "num_outputs": 4,
  "guidance_scale": 7.5,
  "apply_watermark": false,
  "high_noise_frac": 0.8,
  "negative_prompt": "",
  "prompt_strength": 0.8,
  "num_inference_steps": 50
}

npm install replicate

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 fofr/sdxl-color using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/sdxl-color:454561fe18009840dd04e07df5012cdad42b8dfe87e6814c9f8e3e323d9bcfbe",
  {
    input: {
      width: 1024,
      height: 1024,
      prompt: "A TOK red living room, sofa",
      refine: "expert_ensemble_refiner",
      scheduler: "K_EULER",
      lora_scale: 0.6,
      num_outputs: 4,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.8,
      negative_prompt: "",
      prompt_strength: 0.8,
      num_inference_steps: 50
    }
  }
);

// 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.

fofr/sdxl-color:454561fe18009840dd04e07df5012cdad42b8dfe87e6814c9f8e3e323d9bcfbe

pip install replicate

Import the client:

import replicate

Run fofr/sdxl-color using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/sdxl-color:454561fe18009840dd04e07df5012cdad42b8dfe87e6814c9f8e3e323d9bcfbe",
    input={
        "width": 1024,
        "height": 1024,
        "prompt": "A TOK red living room, sofa",
        "refine": "expert_ensemble_refiner",
        "scheduler": "K_EULER",
        "lora_scale": 0.6,
        "num_outputs": 4,
        "guidance_scale": 7.5,
        "apply_watermark": False,
        "high_noise_frac": 0.8,
        "negative_prompt": "",
        "prompt_strength": 0.8,
        "num_inference_steps": 50
    }
)
print(output)

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

Run fofr/sdxl-color 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": "fofr/sdxl-color:454561fe18009840dd04e07df5012cdad42b8dfe87e6814c9f8e3e323d9bcfbe",
    "input": {
      "width": 1024,
      "height": 1024,
      "prompt": "A TOK red living room, sofa",
      "refine": "expert_ensemble_refiner",
      "scheduler": "K_EULER",
      "lora_scale": 0.6,
      "num_outputs": 4,
      "guidance_scale": 7.5,
      "apply_watermark": false,
      "high_noise_frac": 0.8,
      "negative_prompt": "",
      "prompt_strength": 0.8,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

47.7 seconds

Tweak it Share Report

Prediction

Model

ID

gkle6utbetznpforg7mun444qy

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

40.3s

Created

over 1 year ago

Input

width: 1152
height: 768
prompt: A TOK purple landscape
refine: expert_ensemble_refiner
scheduler: K_EULER
lora_scale: 0.6
num_outputs: 4
guidance_scale: 7.5
apply_watermark
high_noise_frac: 0.8
negative_prompt
prompt_strength: 0.8
num_inference_steps: 50

{
  "width": 1152,
  "height": 768,
  "prompt": "A TOK purple landscape",
  "refine": "expert_ensemble_refiner",
  "scheduler": "K_EULER",
  "lora_scale": 0.6,
  "num_outputs": 4,
  "guidance_scale": 7.5,
  "apply_watermark": false,
  "high_noise_frac": 0.8,
  "negative_prompt": "",
  "prompt_strength": 0.8,
  "num_inference_steps": 50
}

npm install replicate

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 fofr/sdxl-color using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/sdxl-color:454561fe18009840dd04e07df5012cdad42b8dfe87e6814c9f8e3e323d9bcfbe",
  {
    input: {
      width: 1152,
      height: 768,
      prompt: "A TOK purple landscape",
      refine: "expert_ensemble_refiner",
      scheduler: "K_EULER",
      lora_scale: 0.6,
      num_outputs: 4,
      guidance_scale: 7.5,
      apply_watermark: false,
      high_noise_frac: 0.8,
      negative_prompt: "",
      prompt_strength: 0.8,
      num_inference_steps: 50
    }
  }
);

// 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.