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melgor /stabledesign_interiordesign:5e13482e
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=melgor/stabledesign_interiordesign
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";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run melgor/stabledesign_interiordesign using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"melgor/stabledesign_interiordesign:5e13482ea317670bfc797bb18bace359860a721a39b5bbcaa1ffcd241d62bca0",
{
input: {
seed: 35853,
prompt: "A vibrant living room with a tropical theme, complete with comfortable rattan furniture, large leafy plants bringing the outdoors in, bright cushions adding pops of color, and bamboo blinds for natural light control.",
img_size: 640,
strength: 0.9,
num_steps: 50,
image_base: "https://replicate.delivery/pbxt/L7mEIfZIesuQxg4nQnFjA2WgQzjePKZ7dTpQ431dd5lhX7iq/7fff3fff3fff0fff01cc8008c138c138847c845f80618100816fc7fb00ff00fd.webp",
guidance_scale: 10
}
}
);
// 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 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 melgor/stabledesign_interiordesign using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"melgor/stabledesign_interiordesign:5e13482ea317670bfc797bb18bace359860a721a39b5bbcaa1ffcd241d62bca0",
input={
"seed": 35853,
"prompt": "A vibrant living room with a tropical theme, complete with comfortable rattan furniture, large leafy plants bringing the outdoors in, bright cushions adding pops of color, and bamboo blinds for natural light control.",
"img_size": 640,
"strength": 0.9,
"num_steps": 50,
"image_base": "https://replicate.delivery/pbxt/L7mEIfZIesuQxg4nQnFjA2WgQzjePKZ7dTpQ431dd5lhX7iq/7fff3fff3fff0fff01cc8008c138c138847c845f80618100816fc7fb00ff00fd.webp",
"guidance_scale": 10
}
)
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 melgor/stabledesign_interiordesign 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": "melgor/stabledesign_interiordesign:5e13482ea317670bfc797bb18bace359860a721a39b5bbcaa1ffcd241d62bca0",
"input": {
"seed": 35853,
"prompt": "A vibrant living room with a tropical theme, complete with comfortable rattan furniture, large leafy plants bringing the outdoors in, bright cushions adding pops of color, and bamboo blinds for natural light control.",
"img_size": 640,
"strength": 0.9,
"num_steps": 50,
"image_base": "https://replicate.delivery/pbxt/L7mEIfZIesuQxg4nQnFjA2WgQzjePKZ7dTpQ431dd5lhX7iq/7fff3fff3fff0fff01cc8008c138c138847c845f80618100816fc7fb00ff00fd.webp",
"guidance_scale": 10
}
}' \
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
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terms of service and privacy policy
Output
{
"completed_at": "2024-06-19T16:14:36.616606Z",
"created_at": "2024-06-19T16:09:04.517000Z",
"data_removed": false,
"error": null,
"id": "zh2fdba30nrgg0cg651adf8q2m",
"input": {
"seed": 35853,
"prompt": "A vibrant living room with a tropical theme, complete with comfortable rattan furniture, large leafy plants bringing the outdoors in, bright cushions adding pops of color, and bamboo blinds for natural light control.",
"img_size": 640,
"strength": 0.9,
"num_steps": 50,
"image_base": "https://replicate.delivery/pbxt/L7mEIfZIesuQxg4nQnFjA2WgQzjePKZ7dTpQ431dd5lhX7iq/7fff3fff3fff0fff01cc8008c138c138847c845f80618100816fc7fb00ff00fd.webp",
"guidance_scale": 10
},
"logs": "/root/.pyenv/versions/3.10.14/lib/python3.10/site-packages/torch/nn/modules/conv.py:456: UserWarning: Plan failed with a cudnnException: CUDNN_BACKEND_EXECUTION_PLAN_DESCRIPTOR: cudnnFinalize Descriptor Failed cudnn_status: CUDNN_STATUS_NOT_SUPPORTED (Triggered internally at ../aten/src/ATen/native/cudnn/Conv_v8.cpp:919.)\nreturn F.conv2d(input, weight, bias, self.stride,\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:07, 6.63it/s]\n 8%|▊ | 4/50 [00:00<00:02, 16.21it/s]\n 14%|█▍ | 7/50 [00:00<00:02, 19.46it/s]\n 20%|██ | 10/50 [00:00<00:01, 21.01it/s]\n 26%|██▌ | 13/50 [00:00<00:01, 22.16it/s]\n 32%|███▏ | 16/50 [00:00<00:01, 22.43it/s]\n 38%|███▊ | 19/50 [00:00<00:01, 22.43it/s]\n 44%|████▍ | 22/50 [00:01<00:01, 22.68it/s]\n 50%|█████ | 25/50 [00:01<00:01, 22.65it/s]\n 56%|█████▌ | 28/50 [00:01<00:00, 22.69it/s]\n 62%|██████▏ | 31/50 [00:01<00:00, 22.91it/s]\n 68%|██████▊ | 34/50 [00:01<00:00, 23.43it/s]\n 74%|███████▍ | 37/50 [00:01<00:00, 23.73it/s]\n 80%|████████ | 40/50 [00:01<00:00, 23.58it/s]\n 86%|████████▌ | 43/50 [00:01<00:00, 23.60it/s]\n 92%|█████████▏| 46/50 [00:02<00:00, 23.92it/s]\n 98%|█████████▊| 49/50 [00:02<00:00, 24.13it/s]\n100%|██████████| 50/50 [00:02<00:00, 22.49it/s]\n 0%| | 0/45 [00:00<?, ?it/s]\n 2%|▏ | 1/45 [00:00<00:06, 6.31it/s]\n 7%|▋ | 3/45 [00:00<00:04, 9.86it/s]\n 11%|█ | 5/45 [00:00<00:03, 11.58it/s]\n 16%|█▌ | 7/45 [00:00<00:03, 12.44it/s]\n 20%|██ | 9/45 [00:00<00:02, 12.92it/s]\n 24%|██▍ | 11/45 [00:00<00:02, 13.24it/s]\n 29%|██▉ | 13/45 [00:01<00:02, 13.43it/s]\n 33%|███▎ | 15/45 [00:01<00:02, 13.55it/s]\n 38%|███▊ | 17/45 [00:01<00:02, 13.61it/s]\n 42%|████▏ | 19/45 [00:01<00:01, 13.65it/s]\n 47%|████▋ | 21/45 [00:01<00:01, 13.68it/s]\n 51%|█████ | 23/45 [00:01<00:01, 13.71it/s]\n 56%|█████▌ | 25/45 [00:01<00:01, 13.74it/s]\n 60%|██████ | 27/45 [00:02<00:01, 13.77it/s]\n 64%|██████▍ | 29/45 [00:02<00:01, 13.77it/s]\n 69%|██████▉ | 31/45 [00:02<00:01, 13.73it/s]\n 73%|███████▎ | 33/45 [00:02<00:00, 13.74it/s]\n 78%|███████▊ | 35/45 [00:02<00:00, 13.74it/s]\n 82%|████████▏ | 37/45 [00:02<00:00, 13.70it/s]\n 87%|████████▋ | 39/45 [00:02<00:00, 13.53it/s]\n 91%|█████████ | 41/45 [00:03<00:00, 13.60it/s]\n 96%|█████████▌| 43/45 [00:03<00:00, 13.63it/s]\n100%|██████████| 45/45 [00:03<00:00, 13.67it/s]\n100%|██████████| 45/45 [00:03<00:00, 13.32it/s]",
"metrics": {
"predict_time": 9.495151756,
"total_time": 332.099606
},
"output": "https://replicate.delivery/pbxt/HZHevsx6TEVFW6QINyzgNfSyrtwcIfknzOoGUDTR1bJYvWAmA/design.png",
"started_at": "2024-06-19T16:14:27.121454Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/zh2fdba30nrgg0cg651adf8q2m",
"cancel": "https://api.replicate.com/v1/predictions/zh2fdba30nrgg0cg651adf8q2m/cancel"
},
"version": "5e13482ea317670bfc797bb18bace359860a721a39b5bbcaa1ffcd241d62bca0"
}Generated in
/root/.pyenv/versions/3.10.14/lib/python3.10/site-packages/torch/nn/modules/conv.py:456: UserWarning: Plan failed with a cudnnException: CUDNN_BACKEND_EXECUTION_PLAN_DESCRIPTOR: cudnnFinalize Descriptor Failed cudnn_status: CUDNN_STATUS_NOT_SUPPORTED (Triggered internally at ../aten/src/ATen/native/cudnn/Conv_v8.cpp:919.)
return F.conv2d(input, weight, bias, self.stride,
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