You're looking at a specific version of this model. Jump to the model overview.
replicategithubwc /dreamlike-photoreal:9c8ae972
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 replicategithubwc/dreamlike-photoreal using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"replicategithubwc/dreamlike-photoreal:9c8ae972b146516029b5ff2abc7b9c0fb4131c10b95c1339144b78b8472f3793",
{
input: {
width: 768,
height: 1024,
prompt: "aurora, girl with super long hair, hair becoming bright stars, in drip modern clothing, intricate, highly detailed, digital painting, artstation, concept art, smooth, sharp focus, illustration, unreal engine 5, 8 k, art by artgerm and greg rutkowski and alphonse mucha",
scheduler: "DPMSolverMultistep",
num_outputs: 4,
guidance_scale: 7.5,
negative_prompt: "out of frame, duplicate, watermark, signature, text",
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 replicategithubwc/dreamlike-photoreal using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"replicategithubwc/dreamlike-photoreal:9c8ae972b146516029b5ff2abc7b9c0fb4131c10b95c1339144b78b8472f3793",
input={
"width": 768,
"height": 1024,
"prompt": "aurora, girl with super long hair, hair becoming bright stars, in drip modern clothing, intricate, highly detailed, digital painting, artstation, concept art, smooth, sharp focus, illustration, unreal engine 5, 8 k, art by artgerm and greg rutkowski and alphonse mucha",
"scheduler": "DPMSolverMultistep",
"num_outputs": 4,
"guidance_scale": 7.5,
"negative_prompt": "out of frame, duplicate, watermark, signature, text",
"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 replicategithubwc/dreamlike-photoreal 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": "replicategithubwc/dreamlike-photoreal:9c8ae972b146516029b5ff2abc7b9c0fb4131c10b95c1339144b78b8472f3793",
"input": {
"width": 768,
"height": 1024,
"prompt": "aurora, girl with super long hair, hair becoming bright stars, in drip modern clothing, intricate, highly detailed, digital painting, artstation, concept art, smooth, sharp focus, illustration, unreal engine 5, 8 k, art by artgerm and greg rutkowski and alphonse mucha",
"scheduler": "DPMSolverMultistep",
"num_outputs": 4,
"guidance_scale": 7.5,
"negative_prompt": "out of frame, duplicate, watermark, signature, text",
"num_inference_steps": 50
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
brew install cog
If 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/replicategithubwc/dreamlike-photoreal@sha256:9c8ae972b146516029b5ff2abc7b9c0fb4131c10b95c1339144b78b8472f3793 \
-i 'width=768' \
-i 'height=1024' \
-i 'prompt="aurora, girl with super long hair, hair becoming bright stars, in drip modern clothing, intricate, highly detailed, digital painting, artstation, concept art, smooth, sharp focus, illustration, unreal engine 5, 8 k, art by artgerm and greg rutkowski and alphonse mucha"' \
-i 'scheduler="DPMSolverMultistep"' \
-i 'num_outputs=4' \
-i 'guidance_scale=7.5' \
-i 'negative_prompt="out of frame, duplicate, watermark, signature, text"' \
-i 'num_inference_steps=50'
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/replicategithubwc/dreamlike-photoreal@sha256:9c8ae972b146516029b5ff2abc7b9c0fb4131c10b95c1339144b78b8472f3793
curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 768, "height": 1024, "prompt": "aurora, girl with super long hair, hair becoming bright stars, in drip modern clothing, intricate, highly detailed, digital painting, artstation, concept art, smooth, sharp focus, illustration, unreal engine 5, 8 k, art by artgerm and greg rutkowski and alphonse mucha", "scheduler": "DPMSolverMultistep", "num_outputs": 4, "guidance_scale": 7.5, "negative_prompt": "out of frame, duplicate, watermark, signature, text", "num_inference_steps": 50 } }' \ 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 $0.069. Alternatively, try out our featured models for free.
By signing in, you agree to our
terms of service and privacy policy
Output
{
"completed_at": "2023-07-14T06:18:17.583070Z",
"created_at": "2023-07-14T06:16:41.251680Z",
"data_removed": false,
"error": null,
"id": "biy2jdtbfgtlw4txsb43knvp2y",
"input": {
"width": 768,
"height": "1024",
"prompt": "aurora, girl with super long hair, hair becoming bright stars, in drip modern clothing, intricate, highly detailed, digital painting, artstation, concept art, smooth, sharp focus, illustration, unreal engine 5, 8 k, art by artgerm and greg rutkowski and alphonse mucha",
"scheduler": "DPMSolverMultistep",
"num_outputs": 4,
"guidance_scale": 7.5,
"negative_prompt": "out of frame, duplicate, watermark, signature, text",
"num_inference_steps": 50
},
"logs": "Using seed: 17744\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:48, 1.01it/s]\n 4%|▍ | 2/50 [00:01<00:33, 1.43it/s]\n 6%|▌ | 3/50 [00:01<00:28, 1.65it/s]\n 8%|▊ | 4/50 [00:02<00:25, 1.77it/s]\n 10%|█ | 5/50 [00:02<00:24, 1.85it/s]\n 12%|█▏ | 6/50 [00:03<00:23, 1.90it/s]\n 14%|█▍ | 7/50 [00:03<00:22, 1.93it/s]\n 16%|█▌ | 8/50 [00:04<00:21, 1.96it/s]\n 18%|█▊ | 9/50 [00:04<00:20, 1.97it/s]\n 20%|██ | 10/50 [00:05<00:20, 1.98it/s]\n 22%|██▏ | 11/50 [00:05<00:19, 1.99it/s]\n 24%|██▍ | 12/50 [00:06<00:19, 1.99it/s]\n 26%|██▌ | 13/50 [00:06<00:18, 1.99it/s]\n 28%|██▊ | 14/50 [00:07<00:18, 2.00it/s]\n 30%|███ | 15/50 [00:07<00:17, 2.00it/s]\n 32%|███▏ | 16/50 [00:08<00:17, 2.00it/s]\n 34%|███▍ | 17/50 [00:08<00:16, 2.00it/s]\n 36%|███▌ | 18/50 [00:09<00:16, 2.00it/s]\n 38%|███▊ | 19/50 [00:09<00:15, 2.00it/s]\n 40%|████ | 20/50 [00:10<00:15, 2.00it/s]\n 42%|████▏ | 21/50 [00:10<00:14, 2.00it/s]\n 44%|████▍ | 22/50 [00:11<00:14, 2.00it/s]\n 46%|████▌ | 23/50 [00:11<00:13, 2.00it/s]\n 48%|████▊ | 24/50 [00:12<00:13, 2.00it/s]\n 50%|█████ | 25/50 [00:12<00:12, 2.00it/s]\n 52%|█████▏ | 26/50 [00:13<00:12, 2.00it/s]\n 54%|█████▍ | 27/50 [00:13<00:11, 2.00it/s]\n 56%|█████▌ | 28/50 [00:14<00:11, 2.00it/s]\n 58%|█████▊ | 29/50 [00:14<00:10, 2.00it/s]\n 60%|██████ | 30/50 [00:15<00:10, 2.00it/s]\n 62%|██████▏ | 31/50 [00:15<00:09, 2.00it/s]\n 64%|██████▍ | 32/50 [00:16<00:09, 2.00it/s]\n 66%|██████▌ | 33/50 [00:16<00:08, 2.00it/s]\n 68%|██████▊ | 34/50 [00:17<00:08, 2.00it/s]\n 70%|███████ | 35/50 [00:17<00:07, 2.00it/s]\n 72%|███████▏ | 36/50 [00:18<00:07, 2.00it/s]\n 74%|███████▍ | 37/50 [00:18<00:06, 2.00it/s]\n 76%|███████▌ | 38/50 [00:19<00:06, 2.00it/s]\n 78%|███████▊ | 39/50 [00:19<00:05, 2.00it/s]\n 80%|████████ | 40/50 [00:20<00:05, 2.00it/s]\n 82%|████████▏ | 41/50 [00:20<00:04, 2.00it/s]\n 84%|████████▍ | 42/50 [00:21<00:04, 2.00it/s]\n 86%|████████▌ | 43/50 [00:21<00:03, 2.00it/s]\n 88%|████████▊ | 44/50 [00:22<00:03, 2.00it/s]\n 90%|█████████ | 45/50 [00:22<00:02, 2.00it/s]\n 92%|█████████▏| 46/50 [00:23<00:02, 2.00it/s]\n 94%|█████████▍| 47/50 [00:23<00:01, 2.00it/s]\n 96%|█████████▌| 48/50 [00:24<00:01, 1.99it/s]\n 98%|█████████▊| 49/50 [00:24<00:00, 2.00it/s]\n100%|██████████| 50/50 [00:25<00:00, 1.99it/s]\n100%|██████████| 50/50 [00:25<00:00, 1.96it/s]",
"metrics": {
"predict_time": 29.125953,
"total_time": 96.33139
},
"output": [
"https://replicate.delivery/pbxt/TZmLfptOma0PPCLm3rcs19et0wM7rf5nXqDGWfCXyCeFVN9JC/out-0.png",
"https://replicate.delivery/pbxt/iAHDSKf2VAT7IqNQ4I20uxg5eUgyjXgvMijKzeKZaufhqmeJC/out-1.png",
"https://replicate.delivery/pbxt/uqmWufJ92fsjepI4SJvzezCQUejAdz1wZV5Fqsw6JUqMVN9JC/out-2.png",
"https://replicate.delivery/pbxt/h0xudOBfnRRpYCBYv5MSag3IQmHRA6baFeB6gHxYT1mpqpPRA/out-3.png"
],
"started_at": "2023-07-14T06:17:48.457117Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/biy2jdtbfgtlw4txsb43knvp2y",
"cancel": "https://api.replicate.com/v1/predictions/biy2jdtbfgtlw4txsb43knvp2y/cancel"
},
"version": "9c8ae972b146516029b5ff2abc7b9c0fb4131c10b95c1339144b78b8472f3793"
}
Using seed: 17744
0%| | 0/50 [00:00<?, ?it/s]
2%|▏ | 1/50 [00:00<00:48, 1.01it/s]
4%|▍ | 2/50 [00:01<00:33, 1.43it/s]
6%|▌ | 3/50 [00:01<00:28, 1.65it/s]
8%|▊ | 4/50 [00:02<00:25, 1.77it/s]
10%|█ | 5/50 [00:02<00:24, 1.85it/s]
12%|█▏ | 6/50 [00:03<00:23, 1.90it/s]
14%|█▍ | 7/50 [00:03<00:22, 1.93it/s]
16%|█▌ | 8/50 [00:04<00:21, 1.96it/s]
18%|█▊ | 9/50 [00:04<00:20, 1.97it/s]
20%|██ | 10/50 [00:05<00:20, 1.98it/s]
22%|██▏ | 11/50 [00:05<00:19, 1.99it/s]
24%|██▍ | 12/50 [00:06<00:19, 1.99it/s]
26%|██▌ | 13/50 [00:06<00:18, 1.99it/s]
28%|██▊ | 14/50 [00:07<00:18, 2.00it/s]
30%|███ | 15/50 [00:07<00:17, 2.00it/s]
32%|███▏ | 16/50 [00:08<00:17, 2.00it/s]
34%|███▍ | 17/50 [00:08<00:16, 2.00it/s]
36%|███▌ | 18/50 [00:09<00:16, 2.00it/s]
38%|███▊ | 19/50 [00:09<00:15, 2.00it/s]
40%|████ | 20/50 [00:10<00:15, 2.00it/s]
42%|████▏ | 21/50 [00:10<00:14, 2.00it/s]
44%|████▍ | 22/50 [00:11<00:14, 2.00it/s]
46%|████▌ | 23/50 [00:11<00:13, 2.00it/s]
48%|████▊ | 24/50 [00:12<00:13, 2.00it/s]
50%|█████ | 25/50 [00:12<00:12, 2.00it/s]
52%|█████▏ | 26/50 [00:13<00:12, 2.00it/s]
54%|█████▍ | 27/50 [00:13<00:11, 2.00it/s]
56%|█████▌ | 28/50 [00:14<00:11, 2.00it/s]
58%|█████▊ | 29/50 [00:14<00:10, 2.00it/s]
60%|██████ | 30/50 [00:15<00:10, 2.00it/s]
62%|██████▏ | 31/50 [00:15<00:09, 2.00it/s]
64%|██████▍ | 32/50 [00:16<00:09, 2.00it/s]
66%|██████▌ | 33/50 [00:16<00:08, 2.00it/s]
68%|██████▊ | 34/50 [00:17<00:08, 2.00it/s]
70%|███████ | 35/50 [00:17<00:07, 2.00it/s]
72%|███████▏ | 36/50 [00:18<00:07, 2.00it/s]
74%|███████▍ | 37/50 [00:18<00:06, 2.00it/s]
76%|███████▌ | 38/50 [00:19<00:06, 2.00it/s]
78%|███████▊ | 39/50 [00:19<00:05, 2.00it/s]
80%|████████ | 40/50 [00:20<00:05, 2.00it/s]
82%|████████▏ | 41/50 [00:20<00:04, 2.00it/s]
84%|████████▍ | 42/50 [00:21<00:04, 2.00it/s]
86%|████████▌ | 43/50 [00:21<00:03, 2.00it/s]
88%|████████▊ | 44/50 [00:22<00:03, 2.00it/s]
90%|█████████ | 45/50 [00:22<00:02, 2.00it/s]
92%|█████████▏| 46/50 [00:23<00:02, 2.00it/s]
94%|█████████▍| 47/50 [00:23<00:01, 2.00it/s]
96%|█████████▌| 48/50 [00:24<00:01, 1.99it/s]
98%|█████████▊| 49/50 [00:24<00:00, 2.00it/s]
100%|██████████| 50/50 [00:25<00:00, 1.99it/s]
100%|██████████| 50/50 [00:25<00:00, 1.96it/s]