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omniedgeio /deepfashionsdxl:f739c74c
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=omniedgeio/deepfashionsdxl
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 omniedgeio/deepfashionsdxl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"omniedgeio/deepfashionsdxl:f739c74c0b1bd61419461ebf0087b55173a214d9df8b2848b728a2c31e36be60",
{
input: {
hdr: 0.5,
width: 1024,
height: 1024,
prompt: "An astronaut riding a rainbow unicorn, cinematic, dramatic",
refine: "base_image_refiner",
scheduler: "K_EULER_ANCESTRAL",
lora_scale: 0.6,
num_outputs: 1,
guidance_scale: 7.5,
apply_watermark: false,
high_noise_frac: 0.8,
negative_prompt: "",
prompt_strength: 0.8,
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 omniedgeio/deepfashionsdxl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"omniedgeio/deepfashionsdxl:f739c74c0b1bd61419461ebf0087b55173a214d9df8b2848b728a2c31e36be60",
input={
"hdr": 0.5,
"width": 1024,
"height": 1024,
"prompt": "An astronaut riding a rainbow unicorn, cinematic, dramatic",
"refine": "base_image_refiner",
"scheduler": "K_EULER_ANCESTRAL",
"lora_scale": 0.6,
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": False,
"high_noise_frac": 0.8,
"negative_prompt": "",
"prompt_strength": 0.8,
"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 omniedgeio/deepfashionsdxl 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": "omniedgeio/deepfashionsdxl:f739c74c0b1bd61419461ebf0087b55173a214d9df8b2848b728a2c31e36be60",
"input": {
"hdr": 0.5,
"width": 1024,
"height": 1024,
"prompt": "An astronaut riding a rainbow unicorn, cinematic, dramatic",
"refine": "base_image_refiner",
"scheduler": "K_EULER_ANCESTRAL",
"lora_scale": 0.6,
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": false,
"high_noise_frac": 0.8,
"negative_prompt": "",
"prompt_strength": 0.8,
"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.
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terms of service and privacy policy
Output
{
"completed_at": "2024-06-07T16:05:44.085706Z",
"created_at": "2024-06-07T16:04:29.115000Z",
"data_removed": false,
"error": null,
"id": "d70wcw5z7drgj0cfydrs8p82xr",
"input": {
"hdr": 0.5,
"width": 1024,
"height": 1024,
"prompt": "An astronaut riding a rainbow unicorn, cinematic, dramatic",
"refine": "base_image_refiner",
"scheduler": "K_EULER_ANCESTRAL",
"lora_scale": 0.6,
"num_outputs": 1,
"guidance_scale": 7.5,
"apply_watermark": false,
"high_noise_frac": 0.8,
"negative_prompt": "",
"prompt_strength": 0.8,
"num_inference_steps": 50
},
"logs": "Using seed: 17852\nPrompt: An astronaut riding a rainbow unicorn, cinematic, dramatic\ntxt2img mode\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:06, 7.97it/s]\n 4%|▍ | 2/50 [00:00<00:05, 8.00it/s]\n 6%|▌ | 3/50 [00:00<00:05, 8.32it/s]\n 8%|▊ | 4/50 [00:00<00:05, 8.49it/s]\n 10%|█ | 5/50 [00:00<00:05, 8.59it/s]\n 12%|█▏ | 6/50 [00:00<00:05, 8.65it/s]\n 14%|█▍ | 7/50 [00:00<00:04, 8.69it/s]\n 16%|█▌ | 8/50 [00:00<00:04, 8.72it/s]\n 18%|█▊ | 9/50 [00:01<00:04, 8.73it/s]\n 20%|██ | 10/50 [00:01<00:04, 8.74it/s]\n 22%|██▏ | 11/50 [00:01<00:04, 8.75it/s]\n 24%|██▍ | 12/50 [00:01<00:04, 8.76it/s]\n 26%|██▌ | 13/50 [00:01<00:04, 8.75it/s]\n 28%|██▊ | 14/50 [00:01<00:04, 8.74it/s]\n 30%|███ | 15/50 [00:01<00:04, 8.74it/s]\n 32%|███▏ | 16/50 [00:01<00:03, 8.74it/s]\n 34%|███▍ | 17/50 [00:01<00:03, 8.74it/s]\n 36%|███▌ | 18/50 [00:02<00:03, 8.75it/s]\n 38%|███▊ | 19/50 [00:02<00:03, 8.75it/s]\n 40%|████ | 20/50 [00:02<00:03, 8.76it/s]\n 42%|████▏ | 21/50 [00:02<00:03, 8.74it/s]\n 44%|████▍ | 22/50 [00:02<00:03, 8.74it/s]\n 46%|████▌ | 23/50 [00:02<00:03, 8.72it/s]\n 48%|████▊ | 24/50 [00:02<00:02, 8.73it/s]\n 50%|█████ | 25/50 [00:02<00:02, 8.72it/s]\n 52%|█████▏ | 26/50 [00:02<00:02, 8.72it/s]\n 54%|█████▍ | 27/50 [00:03<00:02, 8.72it/s]\n 56%|█████▌ | 28/50 [00:03<00:02, 8.73it/s]\n 58%|█████▊ | 29/50 [00:03<00:02, 8.73it/s]\n 60%|██████ | 30/50 [00:03<00:02, 8.72it/s]\n 62%|██████▏ | 31/50 [00:03<00:02, 8.74it/s]\n 64%|██████▍ | 32/50 [00:03<00:02, 8.74it/s]\n 66%|██████▌ | 33/50 [00:03<00:01, 8.73it/s]\n 68%|██████▊ | 34/50 [00:03<00:01, 8.73it/s]\n 70%|███████ | 35/50 [00:04<00:01, 8.74it/s]\n 72%|███████▏ | 36/50 [00:04<00:01, 8.74it/s]\n 74%|███████▍ | 37/50 [00:04<00:01, 8.74it/s]\n 76%|███████▌ | 38/50 [00:04<00:01, 8.75it/s]\n 78%|███████▊ | 39/50 [00:04<00:01, 8.74it/s]\n 80%|████████ | 40/50 [00:04<00:01, 8.75it/s]\n 82%|████████▏ | 41/50 [00:04<00:01, 8.74it/s]\n 84%|████████▍ | 42/50 [00:04<00:00, 8.74it/s]\n 86%|████████▌ | 43/50 [00:04<00:00, 8.74it/s]\n 88%|████████▊ | 44/50 [00:05<00:00, 8.74it/s]\n 90%|█████████ | 45/50 [00:05<00:00, 8.74it/s]\n 92%|█████████▏| 46/50 [00:05<00:00, 8.74it/s]\n 94%|█████████▍| 47/50 [00:05<00:00, 8.73it/s]\n 96%|█████████▌| 48/50 [00:05<00:00, 8.73it/s]\n 98%|█████████▊| 49/50 [00:05<00:00, 8.72it/s]\n100%|██████████| 50/50 [00:05<00:00, 8.73it/s]\n100%|██████████| 50/50 [00:05<00:00, 8.71it/s]\n 0%| | 0/15 [00:00<?, ?it/s]\n 7%|▋ | 1/15 [00:00<00:01, 7.27it/s]\n 13%|█▎ | 2/15 [00:00<00:01, 7.57it/s]\n 20%|██ | 3/15 [00:00<00:01, 7.69it/s]\n 27%|██▋ | 4/15 [00:00<00:01, 7.74it/s]\n 33%|███▎ | 5/15 [00:00<00:01, 7.77it/s]\n 40%|████ | 6/15 [00:00<00:01, 7.78it/s]\n 47%|████▋ | 7/15 [00:00<00:01, 7.79it/s]\n 53%|█████▎ | 8/15 [00:01<00:00, 7.80it/s]\n 60%|██████ | 9/15 [00:01<00:00, 7.80it/s]\n 67%|██████▋ | 10/15 [00:01<00:00, 7.80it/s]\n 73%|███████▎ | 11/15 [00:01<00:00, 7.80it/s]\n 80%|████████ | 12/15 [00:01<00:00, 7.81it/s]\n 87%|████████▋ | 13/15 [00:01<00:00, 7.81it/s]\n 93%|█████████▎| 14/15 [00:01<00:00, 7.80it/s]\n100%|██████████| 15/15 [00:01<00:00, 7.80it/s]\n100%|██████████| 15/15 [00:01<00:00, 7.77it/s]",
"metrics": {
"predict_time": 20.150416,
"total_time": 74.970706
},
"output": [
"https://replicate.delivery/pbxt/92RpLb4Ad1r7CZZJeSoIaVeudGHGevHWHJaoXLAWXAltOc4lA/DF2024-Image.png"
],
"started_at": "2024-06-07T16:05:23.935290Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/d70wcw5z7drgj0cfydrs8p82xr",
"cancel": "https://api.replicate.com/v1/predictions/d70wcw5z7drgj0cfydrs8p82xr/cancel"
},
"version": "f739c74c0b1bd61419461ebf0087b55173a214d9df8b2848b728a2c31e36be60"
}Generated in
Using seed: 17852
Prompt: An astronaut riding a rainbow unicorn, cinematic, dramatic
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