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alexgenovese /test-endpoint:cacd901f
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 alexgenovese/test-endpoint using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"alexgenovese/test-endpoint:cacd901fa63f464ab00d47dcca090658defb4d3d75ff047f564151f854d23764",
{
input: {
seed: 13694,
width: 1024,
height: 1024,
prompt: "A realistic fashion photography of an elegant 30 years old blonde woman in an hotel with one red bag. ((full shot)) 8k uhd, dslr, soft lighting, high quality, Fujifilm XT3. detailed face and detailed skin. cinematic lighting, movie still",
scheduler: "K_EULER",
base_model: "SG161222/RealVisXL_V1.0",
num_outputs: 1,
guidance_scale: 7.5,
apply_watermark: true,
negative_prompt: "overexposed, (deformed iris, deformed pupils, semi-realistic, cgi, 3d, render, sketch, cartoon, drawing, anime:1.4), text, close up, cropped, out of frame, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck",
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.
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 alexgenovese/test-endpoint using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"alexgenovese/test-endpoint:cacd901fa63f464ab00d47dcca090658defb4d3d75ff047f564151f854d23764",
input={
"seed": 13694,
"width": 1024,
"height": 1024,
"prompt": "A realistic fashion photography of an elegant 30 years old blonde woman in an hotel with one red bag. ((full shot)) 8k uhd, dslr, soft lighting, high quality, Fujifilm XT3. detailed face and detailed skin. cinematic lighting, movie still",
"scheduler": "K_EULER",
"base_model": "SG161222/RealVisXL_V1.0",
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": True,
"negative_prompt": "overexposed, (deformed iris, deformed pupils, semi-realistic, cgi, 3d, render, sketch, cartoon, drawing, anime:1.4), text, close up, cropped, out of frame, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck",
"num_inference_steps": 50
}
)
print(output)
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 alexgenovese/test-endpoint 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": "alexgenovese/test-endpoint:cacd901fa63f464ab00d47dcca090658defb4d3d75ff047f564151f854d23764",
"input": {
"seed": 13694,
"width": 1024,
"height": 1024,
"prompt": "A realistic fashion photography of an elegant 30 years old blonde woman in an hotel with one red bag. ((full shot)) 8k uhd, dslr, soft lighting, high quality, Fujifilm XT3. detailed face and detailed skin. cinematic lighting, movie still",
"scheduler": "K_EULER",
"base_model": "SG161222/RealVisXL_V1.0",
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": true,
"negative_prompt": "overexposed, (deformed iris, deformed pupils, semi-realistic, cgi, 3d, render, sketch, cartoon, drawing, anime:1.4), text, close up, cropped, out of frame, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck",
"num_inference_steps": 50
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Add a payment method to run this model.
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Output
{
"completed_at": "2023-09-22T19:47:14.053739Z",
"created_at": "2023-09-22T19:47:01.498135Z",
"data_removed": false,
"error": null,
"id": "nxbfmhrbdvnqo4nlmf5om4jnja",
"input": {
"seed": 13694,
"width": 1024,
"height": 1024,
"prompt": "A realistic fashion photography of an elegant 30 years old blonde woman in an hotel with one red bag. ((full shot)) 8k uhd, dslr, soft lighting, high quality, Fujifilm XT3. detailed face and detailed skin. cinematic lighting, movie still",
"scheduler": "K_EULER",
"base_model": "SG161222/RealVisXL_V1.0",
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": true,
"negative_prompt": "overexposed, (deformed iris, deformed pupils, semi-realistic, cgi, 3d, render, sketch, cartoon, drawing, anime:1.4), text, close up, cropped, out of frame, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck",
"num_inference_steps": 50
},
"logs": "Using seed: 13694\nLoading sdxl pipeline...\nLoading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s]\nLoading pipeline components...: 14%|█▍ | 1/7 [00:00<00:00, 6.45it/s]\nLoading pipeline components...: 43%|████▎ | 3/7 [00:00<00:00, 8.74it/s]\nLoading pipeline components...: 71%|███████▏ | 5/7 [00:00<00:00, 11.25it/s]\nLoading pipeline components...: 100%|██████████| 7/7 [00:02<00:00, 2.32it/s]\nLoading pipeline components...: 100%|██████████| 7/7 [00:02<00:00, 3.08it/s]\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:07, 6.80it/s]\n 4%|▍ | 2/50 [00:00<00:06, 7.74it/s]\n 6%|▌ | 3/50 [00:00<00:05, 8.11it/s]\n 8%|▊ | 4/50 [00:00<00:05, 8.30it/s]\n 10%|█ | 5/50 [00:00<00:05, 8.30it/s]\n 12%|█▏ | 6/50 [00:00<00:05, 8.40it/s]\n 14%|█▍ | 7/50 [00:00<00:05, 8.47it/s]\n 16%|█▌ | 8/50 [00:00<00:04, 8.51it/s]\n 18%|█▊ | 9/50 [00:01<00:04, 8.54it/s]\n 20%|██ | 10/50 [00:01<00:04, 8.55it/s]\n 22%|██▏ | 11/50 [00:01<00:04, 8.56it/s]\n 24%|██▍ | 12/50 [00:01<00:04, 8.43it/s]\n 26%|██▌ | 13/50 [00:01<00:04, 8.44it/s]\n 28%|██▊ | 14/50 [00:01<00:04, 8.30it/s]\n 30%|███ | 15/50 [00:01<00:04, 8.39it/s]\n 32%|███▏ | 16/50 [00:01<00:04, 8.45it/s]\n 34%|███▍ | 17/50 [00:02<00:03, 8.49it/s]\n 36%|███▌ | 18/50 [00:02<00:03, 8.52it/s]\n 38%|███▊ | 19/50 [00:02<00:03, 8.54it/s]\n 40%|████ | 20/50 [00:02<00:03, 8.56it/s]\n 42%|████▏ | 21/50 [00:02<00:03, 8.57it/s]\n 44%|████▍ | 22/50 [00:02<00:03, 8.57it/s]\n 46%|████▌ | 23/50 [00:02<00:03, 8.34it/s]\n 48%|████▊ | 24/50 [00:02<00:03, 8.41it/s]\n 50%|█████ | 25/50 [00:02<00:02, 8.46it/s]\n 52%|█████▏ | 26/50 [00:03<00:02, 8.50it/s]\n 54%|█████▍ | 27/50 [00:03<00:02, 8.53it/s]\n 56%|█████▌ | 28/50 [00:03<00:02, 8.55it/s]\n 58%|█████▊ | 29/50 [00:03<00:02, 8.57it/s]\n 60%|██████ | 30/50 [00:03<00:02, 8.57it/s]\n 62%|██████▏ | 31/50 [00:03<00:02, 8.58it/s]\n 64%|██████▍ | 32/50 [00:03<00:02, 8.58it/s]\n 66%|██████▌ | 33/50 [00:03<00:01, 8.59it/s]\n 68%|██████▊ | 34/50 [00:04<00:01, 8.59it/s]\n 70%|███████ | 35/50 [00:04<00:01, 8.59it/s]\n 72%|███████▏ | 36/50 [00:04<00:01, 8.59it/s]\n 74%|███████▍ | 37/50 [00:04<00:01, 8.59it/s]\n 76%|███████▌ | 38/50 [00:04<00:01, 8.59it/s]\n 78%|███████▊ | 39/50 [00:04<00:01, 8.54it/s]\n 80%|████████ | 40/50 [00:04<00:01, 8.41it/s]\n 82%|████████▏ | 41/50 [00:04<00:01, 8.46it/s]\n 84%|████████▍ | 42/50 [00:04<00:00, 8.50it/s]\n 86%|████████▌ | 43/50 [00:05<00:00, 8.53it/s]\n 88%|████████▊ | 44/50 [00:05<00:00, 8.54it/s]\n 90%|█████████ | 45/50 [00:05<00:00, 8.55it/s]\n 92%|█████████▏| 46/50 [00:05<00:00, 8.56it/s]\n 94%|█████████▍| 47/50 [00:05<00:00, 8.57it/s]\n 96%|█████████▌| 48/50 [00:05<00:00, 8.57it/s]\n 98%|█████████▊| 49/50 [00:05<00:00, 8.56it/s]\n100%|██████████| 50/50 [00:05<00:00, 8.57it/s]\n100%|██████████| 50/50 [00:05<00:00, 8.48it/s]",
"metrics": {
"predict_time": 12.594388,
"total_time": 12.555604
},
"output": [
"https://replicate.delivery/pbxt/NfQhHlnnqoxTXqnbEyJjX1mnBqpOpKZBvx6J925fUTvBF6mRA/out-0.png"
],
"started_at": "2023-09-22T19:47:01.459351Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/nxbfmhrbdvnqo4nlmf5om4jnja",
"cancel": "https://api.replicate.com/v1/predictions/nxbfmhrbdvnqo4nlmf5om4jnja/cancel"
},
"version": "cacd901fa63f464ab00d47dcca090658defb4d3d75ff047f564151f854d23764"
}
Using seed: 13694
Loading sdxl pipeline...
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