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lucataco /realvisxl-v1.0:b4cbb318
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=lucataco/realvisxl-v1.0
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/realvisxl-v1.0 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"lucataco/realvisxl-v1.0:b4cbb3181d03f013ad2b92de9d160373fa820dee177a1e63dd0ae44f592c3833",
{
input: {
seed: 41872,
width: 1024,
height: 1024,
prompt: "dark shot, photo of cute 24 y.o latino male, perfect eyes, skin moles, short hair, looks at viewer, cinematic shot, hard shadows",
scheduler: "DPMSolverMultistep",
guidance_scale: 7,
negative_prompt: "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth",
num_inference_steps: 40
}
}
);
// 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 lucataco/realvisxl-v1.0 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"lucataco/realvisxl-v1.0:b4cbb3181d03f013ad2b92de9d160373fa820dee177a1e63dd0ae44f592c3833",
input={
"seed": 41872,
"width": 1024,
"height": 1024,
"prompt": "dark shot, photo of cute 24 y.o latino male, perfect eyes, skin moles, short hair, looks at viewer, cinematic shot, hard shadows",
"scheduler": "DPMSolverMultistep",
"guidance_scale": 7,
"negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth",
"num_inference_steps": 40
}
)
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/realvisxl-v1.0 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/realvisxl-v1.0:b4cbb3181d03f013ad2b92de9d160373fa820dee177a1e63dd0ae44f592c3833",
"input": {
"seed": 41872,
"width": 1024,
"height": 1024,
"prompt": "dark shot, photo of cute 24 y.o latino male, perfect eyes, skin moles, short hair, looks at viewer, cinematic shot, hard shadows",
"scheduler": "DPMSolverMultistep",
"guidance_scale": 7,
"negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth",
"num_inference_steps": 40
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:
brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/lucataco/realvisxl-v1.0@sha256:b4cbb3181d03f013ad2b92de9d160373fa820dee177a1e63dd0ae44f592c3833 \
-i 'seed=41872' \
-i 'width=1024' \
-i 'height=1024' \
-i 'prompt="dark shot, photo of cute 24 y.o latino male, perfect eyes, skin moles, short hair, looks at viewer, cinematic shot, hard shadows"' \
-i 'scheduler="DPMSolverMultistep"' \
-i 'guidance_scale=7' \
-i 'negative_prompt="(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth"' \
-i 'num_inference_steps=40'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/lucataco/realvisxl-v1.0@sha256:b4cbb3181d03f013ad2b92de9d160373fa820dee177a1e63dd0ae44f592c3833curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "seed": 41872, "width": 1024, "height": 1024, "prompt": "dark shot, photo of cute 24 y.o latino male, perfect eyes, skin moles, short hair, looks at viewer, cinematic shot, hard shadows", "scheduler": "DPMSolverMultistep", "guidance_scale": 7, "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", "num_inference_steps": 40 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Add a payment method to run this model.
Each run costs approximately $0.011. Alternatively, try out our featured models for free.
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Output
{
"completed_at": "2023-09-13T02:38:20.358825Z",
"created_at": "2023-09-13T02:38:13.703003Z",
"data_removed": false,
"error": null,
"id": "eej4ivjbfa5ymeu5tonseb4s3i",
"input": {
"seed": 41872,
"width": 1024,
"height": 1024,
"prompt": "dark shot, photo of cute 24 y.o latino male, perfect eyes, skin moles, short hair, looks at viewer, cinematic shot, hard shadows",
"scheduler": "DPMSolverMultistep",
"guidance_scale": 7,
"negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth",
"num_inference_steps": 40
},
"logs": "Using seed: 41872\n 0%| | 0/40 [00:00<?, ?it/s]\n 2%|▎ | 1/40 [00:00<00:05, 6.89it/s]\n 5%|▌ | 2/40 [00:00<00:04, 7.69it/s]\n 8%|▊ | 3/40 [00:00<00:04, 8.00it/s]\n 10%|█ | 4/40 [00:00<00:04, 8.10it/s]\n 12%|█▎ | 5/40 [00:00<00:04, 8.19it/s]\n 15%|█▌ | 6/40 [00:00<00:04, 8.22it/s]\n 18%|█▊ | 7/40 [00:00<00:04, 7.97it/s]\n 20%|██ | 8/40 [00:01<00:03, 8.05it/s]\n 22%|██▎ | 9/40 [00:01<00:03, 8.02it/s]\n 25%|██▌ | 10/40 [00:01<00:03, 8.04it/s]\n 28%|██▊ | 11/40 [00:01<00:03, 8.12it/s]\n 30%|███ | 12/40 [00:01<00:03, 8.24it/s]\n 32%|███▎ | 13/40 [00:01<00:03, 8.35it/s]\n 35%|███▌ | 14/40 [00:01<00:03, 8.43it/s]\n 38%|███▊ | 15/40 [00:01<00:03, 8.20it/s]\n 40%|████ | 16/40 [00:01<00:02, 8.32it/s]\n 42%|████▎ | 17/40 [00:02<00:02, 8.41it/s]\n 45%|████▌ | 18/40 [00:02<00:02, 8.28it/s]\n 48%|████▊ | 19/40 [00:02<00:02, 8.14it/s]\n 50%|█████ | 20/40 [00:02<00:02, 8.23it/s]\n 52%|█████▎ | 21/40 [00:02<00:02, 7.98it/s]\n 55%|█████▌ | 22/40 [00:02<00:02, 7.67it/s]\n 57%|█████▊ | 23/40 [00:02<00:02, 7.69it/s]\n 60%|██████ | 24/40 [00:02<00:02, 7.67it/s]\n 62%|██████▎ | 25/40 [00:03<00:02, 7.40it/s]\n 65%|██████▌ | 26/40 [00:03<00:01, 7.56it/s]\n 68%|██████▊ | 27/40 [00:03<00:01, 7.85it/s]\n 70%|███████ | 28/40 [00:03<00:01, 8.06it/s]\n 72%|███████▎ | 29/40 [00:03<00:01, 8.20it/s]\n 75%|███████▌ | 30/40 [00:03<00:01, 8.31it/s]\n 78%|███████▊ | 31/40 [00:03<00:01, 8.03it/s]\n 80%|████████ | 32/40 [00:03<00:01, 7.85it/s]\n 82%|████████▎ | 33/40 [00:04<00:00, 7.89it/s]\n 85%|████████▌ | 34/40 [00:04<00:00, 8.00it/s]\n 88%|████████▊ | 35/40 [00:04<00:00, 8.16it/s]\n 90%|█████████ | 36/40 [00:04<00:00, 7.98it/s]\n 92%|█████████▎| 37/40 [00:04<00:00, 7.64it/s]\n 95%|█████████▌| 38/40 [00:04<00:00, 7.49it/s]\n 98%|█████████▊| 39/40 [00:04<00:00, 7.45it/s]\n100%|██████████| 40/40 [00:05<00:00, 7.63it/s]\n100%|██████████| 40/40 [00:05<00:00, 7.95it/s]",
"metrics": {
"predict_time": 6.685543,
"total_time": 6.655822
},
"output": "https://replicate.delivery/pbxt/EpHqLJWB23IRPxP9KXfreAdt1OkRDPmwih3vd8P6wK7bKtjRA/output.png",
"started_at": "2023-09-13T02:38:13.673282Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/eej4ivjbfa5ymeu5tonseb4s3i",
"cancel": "https://api.replicate.com/v1/predictions/eej4ivjbfa5ymeu5tonseb4s3i/cancel"
},
"version": "b4cbb3181d03f013ad2b92de9d160373fa820dee177a1e63dd0ae44f592c3833"
}Generated in
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