A LoRA style based on illustrated buildings from the Simpsons
{
"model": "dev",
"prompt": "a skyscraper in the style of simpsons_buildingsTOK",
"go_fast": false,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3,
"output_quality": 80,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 28
}npm install replicateimport Replicate from "replicate";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run imagesoutofcontrol/simpsons_buildings using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"imagesoutofcontrol/simpsons_buildings:e6bc944c64fe1e53415bcc21008eb424bc2cd48c2722566e6664801e5d67913f",
{
input: {
model: "dev",
prompt: "a skyscraper in the style of simpsons_buildingsTOK",
go_fast: false,
lora_scale: 1,
megapixels: "1",
num_outputs: 1,
aspect_ratio: "1:1",
output_format: "webp",
guidance_scale: 3,
output_quality: 80,
prompt_strength: 0.8,
extra_lora_scale: 1,
num_inference_steps: 28
}
}
);
// 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.
pip install replicateimport replicateRun imagesoutofcontrol/simpsons_buildings using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"imagesoutofcontrol/simpsons_buildings:e6bc944c64fe1e53415bcc21008eb424bc2cd48c2722566e6664801e5d67913f",
input={
"model": "dev",
"prompt": "a skyscraper in the style of simpsons_buildingsTOK",
"go_fast": False,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3,
"output_quality": 80,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 28
}
)
print(output)To learn more, take a look at the guide on getting started with Python.
Run imagesoutofcontrol/simpsons_buildings 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": "imagesoutofcontrol/simpsons_buildings:e6bc944c64fe1e53415bcc21008eb424bc2cd48c2722566e6664801e5d67913f",
"input": {
"model": "dev",
"prompt": "a skyscraper in the style of simpsons_buildingsTOK",
"go_fast": false,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3,
"output_quality": 80,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 28
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
{
"completed_at": "2025-04-29T13:50:31.818739Z",
"created_at": "2025-04-29T13:50:13.157000Z",
"data_removed": false,
"error": null,
"id": "7pkh7dqtmnrm80cpg77sjvjfhr",
"input": {
"model": "dev",
"prompt": "a skyscraper in the style of simpsons_buildingsTOK",
"go_fast": false,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3,
"output_quality": 80,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 28
},
"logs": "free=26700415102976\nDownloading weights\n2025-04-29T13:50:22Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpdhzzmnkv/weights url=https://replicate.delivery/xezq/vTUhOP8lUF6YGxH1lmXfRWfquTWFaBMqgNvBYfqmVEAVee8kC/trained_model.tar\n2025-04-29T13:50:22Z | INFO | [ Cache Service ] enabled=true scheme=http target=hermes.services.svc.cluster.local\n2025-04-29T13:50:23Z | INFO | [ Complete ] dest=/tmp/tmpdhzzmnkv/weights size=\"172 MB\" total_elapsed=0.890s url=https://replicate.delivery/xezq/vTUhOP8lUF6YGxH1lmXfRWfquTWFaBMqgNvBYfqmVEAVee8kC/trained_model.tar\nDownloaded weights in 0.91s\nLoaded LoRAs in 1.48s\nUsing seed: 65219\nPrompt: a skyscraper in the style of simpsons_buildingsTOK\n[!] txt2img mode\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:07, 3.81it/s]\n 7%|▋ | 2/28 [00:00<00:06, 4.32it/s]\n 11%|█ | 3/28 [00:00<00:06, 4.07it/s]\n 14%|█▍ | 4/28 [00:00<00:06, 3.97it/s]\n 18%|█▊ | 5/28 [00:01<00:05, 3.91it/s]\n 21%|██▏ | 6/28 [00:01<00:05, 3.87it/s]\n 25%|██▌ | 7/28 [00:01<00:05, 3.85it/s]\n 29%|██▊ | 8/28 [00:02<00:05, 3.83it/s]\n 32%|███▏ | 9/28 [00:02<00:04, 3.82it/s]\n 36%|███▌ | 10/28 [00:02<00:04, 3.82it/s]\n 39%|███▉ | 11/28 [00:02<00:04, 3.81it/s]\n 43%|████▎ | 12/28 [00:03<00:04, 3.80it/s]\n 46%|████▋ | 13/28 [00:03<00:03, 3.80it/s]\n 50%|█████ | 14/28 [00:03<00:03, 3.80it/s]\n 54%|█████▎ | 15/28 [00:03<00:03, 3.80it/s]\n 57%|█████▋ | 16/28 [00:04<00:03, 3.81it/s]\n 61%|██████ | 17/28 [00:04<00:02, 3.81it/s]\n 64%|██████▍ | 18/28 [00:04<00:02, 3.81it/s]\n 68%|██████▊ | 19/28 [00:04<00:02, 3.80it/s]\n 71%|███████▏ | 20/28 [00:05<00:02, 3.79it/s]\n 75%|███████▌ | 21/28 [00:05<00:01, 3.80it/s]\n 79%|███████▊ | 22/28 [00:05<00:01, 3.80it/s]\n 82%|████████▏ | 23/28 [00:05<00:01, 3.80it/s]\n 86%|████████▌ | 24/28 [00:06<00:01, 3.80it/s]\n 89%|████████▉ | 25/28 [00:06<00:00, 3.80it/s]\n 93%|█████████▎| 26/28 [00:06<00:00, 3.80it/s]\n 96%|█████████▋| 27/28 [00:07<00:00, 3.79it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.80it/s]\n100%|██████████| 28/28 [00:07<00:00, 3.83it/s]\nTotal safe images: 1 out of 1",
"metrics": {
"predict_time": 9.07474967,
"total_time": 18.661739
},
"output": [
"https://replicate.delivery/xezq/Bsr0JfD4depH00Pq4cmdPXCKqVl6fmWtkqM0QJIl2FmPZRPpA/out-0.webp"
],
"started_at": "2025-04-29T13:50:22.743990Z",
"status": "succeeded",
"urls": {
"stream": "https://stream.replicate.com/v1/files/bcwr-uobmhyelthroudjdjjm64lcuxlegfjyo5g3ruwhcicccek52ocva",
"get": "https://api.replicate.com/v1/predictions/7pkh7dqtmnrm80cpg77sjvjfhr",
"cancel": "https://api.replicate.com/v1/predictions/7pkh7dqtmnrm80cpg77sjvjfhr/cancel"
},
"version": "e6bc944c64fe1e53415bcc21008eb424bc2cd48c2722566e6664801e5d67913f"
}free=26700415102976
Downloading weights
2025-04-29T13:50:22Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpdhzzmnkv/weights url=https://replicate.delivery/xezq/vTUhOP8lUF6YGxH1lmXfRWfquTWFaBMqgNvBYfqmVEAVee8kC/trained_model.tar
2025-04-29T13:50:22Z | INFO | [ Cache Service ] enabled=true scheme=http target=hermes.services.svc.cluster.local
2025-04-29T13:50:23Z | INFO | [ Complete ] dest=/tmp/tmpdhzzmnkv/weights size="172 MB" total_elapsed=0.890s url=https://replicate.delivery/xezq/vTUhOP8lUF6YGxH1lmXfRWfquTWFaBMqgNvBYfqmVEAVee8kC/trained_model.tar
Downloaded weights in 0.91s
Loaded LoRAs in 1.48s
Using seed: 65219
Prompt: a skyscraper in the style of simpsons_buildingsTOK
[!] txt2img mode
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Total safe images: 1 out of 1Want to make some of these yourself?
Run this modelThis model is warm. 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 H100. View more.
free=26700415102976
Downloading weights
2025-04-29T13:50:22Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpdhzzmnkv/weights url=https://replicate.delivery/xezq/vTUhOP8lUF6YGxH1lmXfRWfquTWFaBMqgNvBYfqmVEAVee8kC/trained_model.tar
2025-04-29T13:50:22Z | INFO | [ Cache Service ] enabled=true scheme=http target=hermes.services.svc.cluster.local
2025-04-29T13:50:23Z | INFO | [ Complete ] dest=/tmp/tmpdhzzmnkv/weights size="172 MB" total_elapsed=0.890s url=https://replicate.delivery/xezq/vTUhOP8lUF6YGxH1lmXfRWfquTWFaBMqgNvBYfqmVEAVee8kC/trained_model.tar
Downloaded weights in 0.91s
Loaded LoRAs in 1.48s
Using seed: 65219
Prompt: a skyscraper in the style of simpsons_buildingsTOK
[!] txt2img mode
0%| | 0/28 [00:00<?, ?it/s]
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Total safe images: 1 out of 1