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replicategithubwc /dreamlike-diffusion:65e886ff
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=replicategithubwc/dreamlike-diffusion
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";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run replicategithubwc/dreamlike-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"replicategithubwc/dreamlike-diffusion:65e886ff348258be046f8eff2a9ad12cfb666a7becfa9da33dcafaa136059f5c",
{
input: {
width: 768,
height: 1024,
prompt: "calm town in the rural countryside, intricate details, rich colors, beautiful lighting, V-Ray render, sun rays, photorealistic, isometric art, unreal engine,4K results, EOS 50D. iso 1300,photograph, extreme tilt shift, draw by Jacek Yerka, unreal engine",
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.
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 replicategithubwc/dreamlike-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"replicategithubwc/dreamlike-diffusion:65e886ff348258be046f8eff2a9ad12cfb666a7becfa9da33dcafaa136059f5c",
input={
"width": 768,
"height": 1024,
"prompt": "calm town in the rural countryside, intricate details, rich colors, beautiful lighting, V-Ray render, sun rays, photorealistic, isometric art, unreal engine,4K results, EOS 50D. iso 1300,photograph, extreme tilt shift, draw by Jacek Yerka, unreal engine",
"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.
Set the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run replicategithubwc/dreamlike-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": "65e886ff348258be046f8eff2a9ad12cfb666a7becfa9da33dcafaa136059f5c",
"input": {
"width": 768,
"height": 1024,
"prompt": "calm town in the rural countryside, intricate details, rich colors, beautiful lighting, V-Ray render, sun rays, photorealistic, isometric art, unreal engine,4K results, EOS 50D. iso 1300,photograph, extreme tilt shift, draw by Jacek Yerka, unreal engine",
"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/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/replicategithubwc/dreamlike-diffusion@sha256:65e886ff348258be046f8eff2a9ad12cfb666a7becfa9da33dcafaa136059f5c \
-i 'width=768' \
-i 'height=1024' \
-i 'prompt="calm town in the rural countryside, intricate details, rich colors, beautiful lighting, V-Ray render, sun rays, photorealistic, isometric art, unreal engine,4K results, EOS 50D. iso 1300,photograph, extreme tilt shift, draw by Jacek Yerka, unreal engine"' \
-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-diffusion@sha256:65e886ff348258be046f8eff2a9ad12cfb666a7becfa9da33dcafaa136059f5ccurl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 768, "height": 1024, "prompt": "calm town in the rural countryside, intricate details, rich colors, beautiful lighting, V-Ray render, sun rays, photorealistic, isometric art, unreal engine,4K results, EOS 50D. iso 1300,photograph, extreme tilt shift, draw by Jacek Yerka, unreal engine", "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 $0.14. Alternatively, try out our featured models for free.
Sign in with GitHub
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terms of service and privacy policy
Output
{
"completed_at": "2023-07-18T07:47:15.345870Z",
"created_at": "2023-07-18T07:44:39.155781Z",
"data_removed": false,
"error": null,
"id": "r5mwd4tbddc7ys3ed6d66qw7vu",
"input": {
"width": 768,
"height": "1024",
"prompt": "calm town in the rural countryside, intricate details, rich colors, beautiful lighting, V-Ray render, sun rays, photorealistic, isometric art, unreal engine,4K results, EOS 50D. iso 1300,photograph, extreme tilt shift, draw by Jacek Yerka, unreal engine",
"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: 33701\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:47, 1.02it/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<00:26, 1.77it/s]\n 10%|█ | 5/50 [00:02<00:24, 1.84it/s]\n 12%|█▏ | 6/50 [00:03<00:23, 1.89it/s]\n 14%|█▍ | 7/50 [00:03<00:22, 1.92it/s]\n 16%|█▌ | 8/50 [00:04<00:21, 1.94it/s]\n 18%|█▊ | 9/50 [00:04<00:20, 1.95it/s]\n 20%|██ | 10/50 [00:05<00:20, 1.96it/s]\n 22%|██▏ | 11/50 [00:06<00:19, 1.97it/s]\n 24%|██▍ | 12/50 [00:06<00:19, 1.97it/s]\n 26%|██▌ | 13/50 [00:07<00:18, 1.98it/s]\n 28%|██▊ | 14/50 [00:07<00:18, 1.98it/s]\n 30%|███ | 15/50 [00:08<00:17, 1.98it/s]\n 32%|███▏ | 16/50 [00:08<00:17, 1.98it/s]\n 34%|███▍ | 17/50 [00:09<00:16, 1.98it/s]\n 36%|███▌ | 18/50 [00:09<00:16, 1.98it/s]\n 38%|███▊ | 19/50 [00:10<00:15, 1.98it/s]\n 40%|████ | 20/50 [00:10<00:15, 1.98it/s]\n 42%|████▏ | 21/50 [00:11<00:14, 1.98it/s]\n 44%|████▍ | 22/50 [00:11<00:14, 1.98it/s]\n 46%|████▌ | 23/50 [00:12<00:13, 1.98it/s]\n 48%|████▊ | 24/50 [00:12<00:13, 1.98it/s]\n 50%|█████ | 25/50 [00:13<00:12, 1.98it/s]\n 52%|█████▏ | 26/50 [00:13<00:12, 1.98it/s]\n 54%|█████▍ | 27/50 [00:14<00:11, 1.98it/s]\n 56%|█████▌ | 28/50 [00:14<00:11, 1.98it/s]\n 58%|█████▊ | 29/50 [00:15<00:10, 1.98it/s]\n 60%|██████ | 30/50 [00:15<00:10, 1.98it/s]\n 62%|██████▏ | 31/50 [00:16<00:09, 1.98it/s]\n 64%|██████▍ | 32/50 [00:16<00:09, 1.98it/s]\n 66%|██████▌ | 33/50 [00:17<00:08, 1.98it/s]\n 68%|██████▊ | 34/50 [00:17<00:08, 1.98it/s]\n 70%|███████ | 35/50 [00:18<00:07, 1.98it/s]\n 72%|███████▏ | 36/50 [00:18<00:07, 1.98it/s]\n 74%|███████▍ | 37/50 [00:19<00:06, 1.98it/s]\n 76%|███████▌ | 38/50 [00:19<00:06, 1.98it/s]\n 78%|███████▊ | 39/50 [00:20<00:05, 1.98it/s]\n 80%|████████ | 40/50 [00:20<00:05, 1.98it/s]\n 82%|████████▏ | 41/50 [00:21<00:04, 1.98it/s]\n 84%|████████▍ | 42/50 [00:21<00:04, 1.98it/s]\n 86%|████████▌ | 43/50 [00:22<00:03, 1.98it/s]\n 88%|████████▊ | 44/50 [00:22<00:03, 1.98it/s]\n 90%|█████████ | 45/50 [00:23<00:02, 1.98it/s]\n 92%|█████████▏| 46/50 [00:23<00:02, 1.98it/s]\n 94%|█████████▍| 47/50 [00:24<00:01, 1.98it/s]\n 96%|█████████▌| 48/50 [00:24<00:01, 1.98it/s]\n 98%|█████████▊| 49/50 [00:25<00:00, 1.98it/s]\n100%|██████████| 50/50 [00:25<00:00, 1.98it/s]\n100%|██████████| 50/50 [00:25<00:00, 1.95it/s]",
"metrics": {
"predict_time": 30.48311,
"total_time": 156.190089
},
"output": [
"https://replicate.delivery/pbxt/zmydefeLDuGf5TYZWCdjdM3OUMzHIXUfhnDthDSQUP9Ew6HKC/out-0.png",
"https://replicate.delivery/pbxt/IXkxoHImKwJAFR6BI1zbTMzCQAeJ2XuwfTP7qicNvniBWfhiA/out-1.png",
"https://replicate.delivery/pbxt/9Lf1gPcZvCXZWqFmnjX4eiHriwre1DmeZPLyIk7SM6vIY9DFB/out-2.png",
"https://replicate.delivery/pbxt/F88iIhRHViYXOh9GyyLXI35wSI355n5auQK2nnuy81eBrfQRA/out-3.png"
],
"started_at": "2023-07-18T07:46:44.862760Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/r5mwd4tbddc7ys3ed6d66qw7vu",
"cancel": "https://api.replicate.com/v1/predictions/r5mwd4tbddc7ys3ed6d66qw7vu/cancel"
},
"version": "65e886ff348258be046f8eff2a9ad12cfb666a7becfa9da33dcafaa136059f5c"
}Generated in
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