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lucataco /style-aligned:4ae87bee
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=lucataco/style-aligned
or set up a project from scratch
Install Replicate’s Node.js client library:
npm install replicateSet 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 lucataco/style-aligned using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"lucataco/style-aligned:4ae87bee984bc5346c5ec8d6f8573825d0c602b5f5f82fc15b12460b997f90c8",
{
input: {
seed: 7998,
image: "https://replicate.delivery/pbxt/K23WY2plxah7r8TASoTXvBGH6nZVZmnrLXBlRNt3cP7DyoK3/medieval-bed.jpeg",
width: 768,
height: 768,
prompt: "A man working on a laptop\nA man eats pizza\nA woman playing on saxophone",
style_prompt: "medieval painting",
image_subject: "None",
guidance_scale: 7,
negative_prompt: "low-resolution",
shared_score_scale: 1,
shared_score_shift: 2,
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.
Install Replicate’s Python client library:
pip install replicateSet 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 replicateRun lucataco/style-aligned using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"lucataco/style-aligned:4ae87bee984bc5346c5ec8d6f8573825d0c602b5f5f82fc15b12460b997f90c8",
input={
"seed": 7998,
"image": "https://replicate.delivery/pbxt/K23WY2plxah7r8TASoTXvBGH6nZVZmnrLXBlRNt3cP7DyoK3/medieval-bed.jpeg",
"width": 768,
"height": 768,
"prompt": "A man working on a laptop\nA man eats pizza\nA woman playing on saxophone",
"style_prompt": "medieval painting",
"image_subject": "None",
"guidance_scale": 7,
"negative_prompt": "low-resolution",
"shared_score_scale": 1,
"shared_score_shift": 2,
"num_inference_steps": 50
}
)
print(output)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 lucataco/style-aligned 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": "lucataco/style-aligned:4ae87bee984bc5346c5ec8d6f8573825d0c602b5f5f82fc15b12460b997f90c8",
"input": {
"seed": 7998,
"image": "https://replicate.delivery/pbxt/K23WY2plxah7r8TASoTXvBGH6nZVZmnrLXBlRNt3cP7DyoK3/medieval-bed.jpeg",
"width": 768,
"height": 768,
"prompt": "A man working on a laptop\\nA man eats pizza\\nA woman playing on saxophone",
"style_prompt": "medieval painting",
"image_subject": "None",
"guidance_scale": 7,
"negative_prompt": "low-resolution",
"shared_score_scale": 1,
"shared_score_shift": 2,
"num_inference_steps": 50
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Add a payment method to run this model.
Sign in with GitHub
By signing in, you agree to our
terms of service and privacy policy
Output
{
"completed_at": "2023-12-11T21:16:26.510044Z",
"created_at": "2023-12-11T21:15:45.036722Z",
"data_removed": false,
"error": null,
"id": "avdn7nrbhnzisx2twbi7xxoe74",
"input": {
"seed": 7998,
"image": "https://replicate.delivery/pbxt/K23WY2plxah7r8TASoTXvBGH6nZVZmnrLXBlRNt3cP7DyoK3/medieval-bed.jpeg",
"width": 768,
"height": 768,
"prompt": "A man working on a laptop\nA man eats pizza\nA woman playing on saxophone",
"style_prompt": "medieval painting",
"image_subject": "None",
"guidance_scale": 7,
"negative_prompt": "low-resolution",
"shared_score_scale": 1,
"shared_score_shift": 2,
"num_inference_steps": 50
},
"logs": "Using seed: 7998\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:10, 4.57it/s]\n 4%|▍ | 2/50 [00:00<00:10, 4.53it/s]\n 6%|▌ | 3/50 [00:00<00:10, 4.47it/s]\n 8%|▊ | 4/50 [00:00<00:10, 4.50it/s]\n 10%|█ | 5/50 [00:01<00:09, 4.53it/s]\n 12%|█▏ | 6/50 [00:01<00:09, 4.56it/s]\n 14%|█▍ | 7/50 [00:01<00:09, 4.58it/s]\n 16%|█▌ | 8/50 [00:01<00:09, 4.58it/s]\n 18%|█▊ | 9/50 [00:01<00:08, 4.59it/s]\n 20%|██ | 10/50 [00:02<00:08, 4.63it/s]\n 22%|██▏ | 11/50 [00:02<00:08, 4.65it/s]\n 24%|██▍ | 12/50 [00:02<00:08, 4.63it/s]\n 26%|██▌ | 13/50 [00:02<00:08, 4.60it/s]\n 28%|██▊ | 14/50 [00:03<00:07, 4.61it/s]\n 30%|███ | 15/50 [00:03<00:07, 4.62it/s]\n 32%|███▏ | 16/50 [00:03<00:07, 4.64it/s]\n 34%|███▍ | 17/50 [00:03<00:07, 4.62it/s]\n 36%|███▌ | 18/50 [00:03<00:06, 4.61it/s]\n 38%|███▊ | 19/50 [00:04<00:06, 4.63it/s]\n 40%|████ | 20/50 [00:04<00:06, 4.64it/s]\n 42%|████▏ | 21/50 [00:04<00:06, 4.66it/s]\n 44%|████▍ | 22/50 [00:04<00:06, 4.64it/s]\n 46%|████▌ | 23/50 [00:04<00:05, 4.64it/s]\n 48%|████▊ | 24/50 [00:05<00:05, 4.64it/s]\n 50%|█████ | 25/50 [00:05<00:05, 4.66it/s]\n 52%|█████▏ | 26/50 [00:05<00:05, 4.64it/s]\n 54%|█████▍ | 27/50 [00:05<00:04, 4.63it/s]\n 56%|█████▌ | 28/50 [00:06<00:04, 4.65it/s]\n 58%|█████▊ | 29/50 [00:06<00:04, 4.65it/s]\n 60%|██████ | 30/50 [00:06<00:04, 4.68it/s]\n 62%|██████▏ | 31/50 [00:06<00:04, 4.67it/s]\n 64%|██████▍ | 32/50 [00:06<00:03, 4.66it/s]\n 66%|██████▌ | 33/50 [00:07<00:03, 4.68it/s]\n 68%|██████▊ | 34/50 [00:07<00:03, 4.69it/s]\n 70%|███████ | 35/50 [00:07<00:03, 4.70it/s]\n 72%|███████▏ | 36/50 [00:07<00:02, 4.68it/s]\n 74%|███████▍ | 37/50 [00:07<00:02, 4.68it/s]\n 76%|███████▌ | 38/50 [00:08<00:02, 4.69it/s]\n 78%|███████▊ | 39/50 [00:08<00:02, 4.68it/s]\n 80%|████████ | 40/50 [00:08<00:02, 4.69it/s]\n 82%|████████▏ | 41/50 [00:08<00:01, 4.68it/s]\n 84%|████████▍ | 42/50 [00:09<00:01, 4.69it/s]\n 86%|████████▌ | 43/50 [00:09<00:01, 4.70it/s]\n 88%|████████▊ | 44/50 [00:09<00:01, 4.69it/s]\n 90%|█████████ | 45/50 [00:09<00:01, 4.66it/s]\n 92%|█████████▏| 46/50 [00:09<00:00, 4.65it/s]\n 94%|█████████▍| 47/50 [00:10<00:00, 4.63it/s]\n 96%|█████████▌| 48/50 [00:10<00:00, 4.63it/s]\n 98%|█████████▊| 49/50 [00:10<00:00, 4.63it/s]\n100%|██████████| 50/50 [00:10<00:00, 4.63it/s]\n100%|██████████| 50/50 [00:10<00:00, 4.64it/s]\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:25, 1.89it/s]\n 4%|▍ | 2/50 [00:01<00:25, 1.89it/s]\n 6%|▌ | 3/50 [00:01<00:24, 1.89it/s]\n 8%|▊ | 4/50 [00:02<00:24, 1.89it/s]\n 10%|█ | 5/50 [00:02<00:23, 1.89it/s]\n 12%|█▏ | 6/50 [00:03<00:23, 1.89it/s]\n 14%|█▍ | 7/50 [00:03<00:22, 1.89it/s]\n 16%|█▌ | 8/50 [00:04<00:22, 1.89it/s]\n 18%|█▊ | 9/50 [00:04<00:21, 1.89it/s]\n 20%|██ | 10/50 [00:05<00:21, 1.89it/s]\n 22%|██▏ | 11/50 [00:05<00:20, 1.88it/s]\n 24%|██▍ | 12/50 [00:06<00:20, 1.88it/s]\n 26%|██▌ | 13/50 [00:06<00:19, 1.89it/s]\n 28%|██▊ | 14/50 [00:07<00:19, 1.89it/s]\n 30%|███ | 15/50 [00:07<00:18, 1.89it/s]\n 32%|███▏ | 16/50 [00:08<00:18, 1.89it/s]\n 34%|███▍ | 17/50 [00:09<00:17, 1.89it/s]\n 36%|███▌ | 18/50 [00:09<00:16, 1.88it/s]\n 38%|███▊ | 19/50 [00:10<00:16, 1.89it/s]\n 40%|████ | 20/50 [00:10<00:15, 1.89it/s]\n 42%|████▏ | 21/50 [00:11<00:15, 1.89it/s]\n 44%|████▍ | 22/50 [00:11<00:14, 1.89it/s]\n 46%|████▌ | 23/50 [00:12<00:14, 1.89it/s]\n 48%|████▊ | 24/50 [00:12<00:13, 1.89it/s]\n 50%|█████ | 25/50 [00:13<00:13, 1.89it/s]\n 52%|█████▏ | 26/50 [00:13<00:12, 1.89it/s]\n 54%|█████▍ | 27/50 [00:14<00:12, 1.89it/s]\n 56%|█████▌ | 28/50 [00:14<00:11, 1.89it/s]\n 58%|█████▊ | 29/50 [00:15<00:11, 1.89it/s]\n 60%|██████ | 30/50 [00:15<00:10, 1.88it/s]\n 62%|██████▏ | 31/50 [00:16<00:10, 1.88it/s]\n 64%|██████▍ | 32/50 [00:16<00:09, 1.88it/s]\n 66%|██████▌ | 33/50 [00:17<00:09, 1.88it/s]\n 68%|██████▊ | 34/50 [00:18<00:08, 1.88it/s]\n 70%|███████ | 35/50 [00:18<00:07, 1.88it/s]\n 72%|███████▏ | 36/50 [00:19<00:07, 1.88it/s]\n 74%|███████▍ | 37/50 [00:19<00:06, 1.88it/s]\n 76%|███████▌ | 38/50 [00:20<00:06, 1.88it/s]\n 78%|███████▊ | 39/50 [00:20<00:05, 1.88it/s]\n 80%|████████ | 40/50 [00:21<00:05, 1.88it/s]\n 82%|████████▏ | 41/50 [00:21<00:04, 1.88it/s]\n 84%|████████▍ | 42/50 [00:22<00:04, 1.88it/s]\n 86%|████████▌ | 43/50 [00:22<00:03, 1.88it/s]\n 88%|████████▊ | 44/50 [00:23<00:03, 1.88it/s]\n 90%|█████████ | 45/50 [00:23<00:02, 1.88it/s]\n 92%|█████████▏| 46/50 [00:24<00:02, 1.88it/s]\n 94%|█████████▍| 47/50 [00:24<00:01, 1.88it/s]\n 96%|█████████▌| 48/50 [00:25<00:01, 1.88it/s]\n 98%|█████████▊| 49/50 [00:25<00:00, 1.88it/s]\n100%|██████████| 50/50 [00:26<00:00, 1.88it/s]\n100%|██████████| 50/50 [00:26<00:00, 1.88it/s]",
"metrics": {
"predict_time": 41.460926,
"total_time": 41.473322
},
"output": [
"https://replicate.delivery/pbxt/KleYIJ8ZZ3yHAKndOeGg4bpHWjIbfbu3MZ7yMSrxffPGFXKQC/output-1.png",
"https://replicate.delivery/pbxt/8n0uU9xHHfzGXyJIkAOu4HOagJilKNaDCotUpIo8K27UcpAJA/output-2.png",
"https://replicate.delivery/pbxt/g23clZinoZIzANqxp1iUDjneJu2lfGeYGAQVCY3PRMdSxlCkA/output-3.png"
],
"started_at": "2023-12-11T21:15:45.049118Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/avdn7nrbhnzisx2twbi7xxoe74",
"cancel": "https://api.replicate.com/v1/predictions/avdn7nrbhnzisx2twbi7xxoe74/cancel"
},
"version": "4ae87bee984bc5346c5ec8d6f8573825d0c602b5f5f82fc15b12460b997f90c8"
}Generated in
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