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zust-ai /zust-diffusion:8eea01f7
Input
Run this model in Node.js with one line of code:
npm install replicate
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import Replicate from "replicate";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run zust-ai/zust-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"zust-ai/zust-diffusion:8eea01f757ebf533880a3ff1c9d30389d804bb3f38ce0691c4fdd69404fa17d2",
{
input: {
width: 1024,
height: 1024,
prompt: "trolley suitcase on a mountain rock with hot air balloons in the bkue sky",
subjects: "[{\"top\": 0.3583984375, \"left\": 0.546875, \"scale\": 0.0009765625, \"image_url\": \"https://raw.githubusercontent.com/zust-ai/product-ai-training/main/test/test_subject.png\"}]",
pipe_type: "sdxl",
with_detail: false,
cleanup_mask: "lorem ipsum",
is_heartbeat: false,
cleanup_image: "lorem ipsum",
cleanup_dilate: 5,
negative_prompt: "floating objects, levitate, ugly, blur, text, signature, watermark, bad quality, lowres, worst quality, drawing",
refiner_strength: 0.3,
firstpass_fix_dilate: 11,
num_images_per_prompt: 2,
cleanup_guidance_scale: 7,
cleanup_inference_steps: 25,
refiner_inference_steps: 30,
refiner_prompt_strength: 5,
cleanup_denoise_strength: 0.8,
firstpass_inference_steps: 20,
firstpass_prompt_strength: 5,
firstpass_dilate_iterations: 5,
firstpass_subject_control_strength: 0.5
}
}
);
// 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 replicate
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import replicate
Run zust-ai/zust-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"zust-ai/zust-diffusion:8eea01f757ebf533880a3ff1c9d30389d804bb3f38ce0691c4fdd69404fa17d2",
input={
"width": 1024,
"height": 1024,
"prompt": "trolley suitcase on a mountain rock with hot air balloons in the bkue sky",
"subjects": "[{\"top\": 0.3583984375, \"left\": 0.546875, \"scale\": 0.0009765625, \"image_url\": \"https://raw.githubusercontent.com/zust-ai/product-ai-training/main/test/test_subject.png\"}]",
"pipe_type": "sdxl",
"with_detail": False,
"cleanup_mask": "lorem ipsum",
"is_heartbeat": False,
"cleanup_image": "lorem ipsum",
"cleanup_dilate": 5,
"negative_prompt": "floating objects, levitate, ugly, blur, text, signature, watermark, bad quality, lowres, worst quality, drawing",
"refiner_strength": 0.3,
"firstpass_fix_dilate": 11,
"num_images_per_prompt": 2,
"cleanup_guidance_scale": 7,
"cleanup_inference_steps": 25,
"refiner_inference_steps": 30,
"refiner_prompt_strength": 5,
"cleanup_denoise_strength": 0.8,
"firstpass_inference_steps": 20,
"firstpass_prompt_strength": 5,
"firstpass_dilate_iterations": 5,
"firstpass_subject_control_strength": 0.5
}
)
# 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.
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run zust-ai/zust-diffusion 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": "zust-ai/zust-diffusion:8eea01f757ebf533880a3ff1c9d30389d804bb3f38ce0691c4fdd69404fa17d2",
"input": {
"width": 1024,
"height": 1024,
"prompt": "trolley suitcase on a mountain rock with hot air balloons in the bkue sky",
"subjects": "[{\\"top\\": 0.3583984375, \\"left\\": 0.546875, \\"scale\\": 0.0009765625, \\"image_url\\": \\"https://raw.githubusercontent.com/zust-ai/product-ai-training/main/test/test_subject.png\\"}]",
"pipe_type": "sdxl",
"with_detail": false,
"cleanup_mask": "lorem ipsum",
"is_heartbeat": false,
"cleanup_image": "lorem ipsum",
"cleanup_dilate": 5,
"negative_prompt": "floating objects, levitate, ugly, blur, text, signature, watermark, bad quality, lowres, worst quality, drawing",
"refiner_strength": 0.3,
"firstpass_fix_dilate": 11,
"num_images_per_prompt": 2,
"cleanup_guidance_scale": 7,
"cleanup_inference_steps": 25,
"refiner_inference_steps": 30,
"refiner_prompt_strength": 5,
"cleanup_denoise_strength": 0.8,
"firstpass_inference_steps": 20,
"firstpass_prompt_strength": 5,
"firstpass_dilate_iterations": 5,
"firstpass_subject_control_strength": 0.5
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
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Output
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