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tstramer /arcane-diffusion:4cbb3f91
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=tstramer/arcane-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 tstramer/arcane-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"tstramer/arcane-diffusion:4cbb3f91f9ba049151efb8922fdecc6703d419ea682b87ff94c5876addabfb19",
{
input: {
width: 512,
height: 512,
prompt: "harry potter, arcane style, intricate highly detailed digital painting artstation concept art smooth sharp focus illustration Unreal Engine 5 8K",
scheduler: "K-LMS",
num_outputs: 1,
guidance_scale: 7.5,
prompt_strength: 0.8,
num_inference_steps: 150
}
}
);
console.log(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 tstramer/arcane-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"tstramer/arcane-diffusion:4cbb3f91f9ba049151efb8922fdecc6703d419ea682b87ff94c5876addabfb19",
input={
"width": 512,
"height": 512,
"prompt": "harry potter, arcane style, intricate highly detailed digital painting artstation concept art smooth sharp focus illustration Unreal Engine 5 8K",
"scheduler": "K-LMS",
"num_outputs": 1,
"guidance_scale": 7.5,
"prompt_strength": 0.8,
"num_inference_steps": 150
}
)
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 tstramer/arcane-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": "4cbb3f91f9ba049151efb8922fdecc6703d419ea682b87ff94c5876addabfb19",
"input": {
"width": 512,
"height": 512,
"prompt": "harry potter, arcane style, intricate highly detailed digital painting artstation concept art smooth sharp focus illustration Unreal Engine 5 8K",
"scheduler": "K-LMS",
"num_outputs": 1,
"guidance_scale": 7.5,
"prompt_strength": 0.8,
"num_inference_steps": 150
}
}' \
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/tstramer/arcane-diffusion@sha256:4cbb3f91f9ba049151efb8922fdecc6703d419ea682b87ff94c5876addabfb19 \
-i 'width=512' \
-i 'height=512' \
-i 'prompt="harry potter, arcane style, intricate highly detailed digital painting artstation concept art smooth sharp focus illustration Unreal Engine 5 8K"' \
-i 'scheduler="K-LMS"' \
-i 'num_outputs=1' \
-i 'guidance_scale=7.5' \
-i 'prompt_strength=0.8' \
-i 'num_inference_steps=150'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/tstramer/arcane-diffusion@sha256:4cbb3f91f9ba049151efb8922fdecc6703d419ea682b87ff94c5876addabfb19curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "width": 512, "height": 512, "prompt": "harry potter, arcane style, intricate highly detailed digital painting artstation concept art smooth sharp focus illustration Unreal Engine 5 8K", "scheduler": "K-LMS", "num_outputs": 1, "guidance_scale": 7.5, "prompt_strength": 0.8, "num_inference_steps": 150 } }' \ 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 $0.035. Alternatively, try out our featured models for free.
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Output
{
"completed_at": "2022-11-08T01:58:18.276112Z",
"created_at": "2022-11-08T01:55:35.056826Z",
"data_removed": false,
"error": null,
"id": "2ggapwprc5cmrpxijznihpzrw4",
"input": {
"width": 512,
"height": 512,
"prompt": "harry potter, arcane style, intricate highly detailed digital painting artstation concept art smooth sharp focus illustration Unreal Engine 5 8K",
"scheduler": "K-LMS",
"num_outputs": 1,
"guidance_scale": 7.5,
"prompt_strength": 0.8,
"num_inference_steps": "150"
},
"logs": "Using seed: 60774\n\n 0%| | 0/150 [00:00<?, ?it/s]\n 1%| | 1/150 [00:02<05:26, 2.19s/it]\n 2%|▏ | 3/150 [00:02<01:31, 1.60it/s]\n 3%|▎ | 5/150 [00:02<00:49, 2.93it/s]\n 5%|▍ | 7/150 [00:02<00:32, 4.38it/s]\n 6%|▌ | 9/150 [00:02<00:24, 5.86it/s]\n 7%|▋ | 11/150 [00:02<00:19, 7.28it/s]\n 9%|▊ | 13/150 [00:03<00:15, 8.57it/s]\n 10%|█ | 15/150 [00:03<00:13, 9.69it/s]\n 11%|█▏ | 17/150 [00:03<00:12, 10.63it/s]\n 13%|█▎ | 19/150 [00:03<00:11, 11.39it/s]\n 14%|█▍ | 21/150 [00:03<00:10, 11.92it/s]\n 15%|█▌ | 23/150 [00:03<00:10, 12.35it/s]\n 17%|█▋ | 25/150 [00:03<00:09, 12.73it/s]\n 18%|█▊ | 27/150 [00:04<00:09, 12.88it/s]\n 19%|█▉ | 29/150 [00:04<00:09, 12.68it/s]\n 21%|██ | 31/150 [00:04<00:09, 12.99it/s]\n 22%|██▏ | 33/150 [00:04<00:08, 13.24it/s]\n 23%|██▎ | 35/150 [00:04<00:08, 13.29it/s]\n 25%|██▍ | 37/150 [00:04<00:08, 13.46it/s]\n 26%|██▌ | 39/150 [00:05<00:08, 13.51it/s]\n 27%|██▋ | 41/150 [00:05<00:08, 13.52it/s]\n 29%|██▊ | 43/150 [00:05<00:07, 13.57it/s]\n 30%|███ | 45/150 [00:05<00:07, 13.65it/s]\n 31%|███▏ | 47/150 [00:05<00:07, 13.64it/s]\n 33%|███▎ | 49/150 [00:05<00:07, 13.54it/s]\n 34%|███▍ | 51/150 [00:05<00:07, 13.58it/s]\n 35%|███▌ | 53/150 [00:06<00:07, 13.66it/s]\n 37%|███▋ | 55/150 [00:06<00:06, 13.72it/s]\n 38%|███▊ | 57/150 [00:06<00:07, 12.92it/s]\n 39%|███▉ | 59/150 [00:06<00:07, 12.22it/s]\n 41%|████ | 61/150 [00:06<00:07, 12.41it/s]\n 42%|████▏ | 63/150 [00:06<00:06, 12.61it/s]\n 43%|████▎ | 65/150 [00:07<00:06, 12.90it/s]\n 45%|████▍ | 67/150 [00:07<00:06, 13.17it/s]\n 46%|████▌ | 69/150 [00:07<00:06, 13.32it/s]\n 47%|████▋ | 71/150 [00:07<00:05, 13.50it/s]\n 49%|████▊ | 73/150 [00:07<00:05, 13.61it/s]\n 50%|█████ | 75/150 [00:07<00:05, 13.47it/s]\n 51%|█████▏ | 77/150 [00:07<00:05, 13.46it/s]\n 53%|█████▎ | 79/150 [00:08<00:05, 13.55it/s]\n 54%|█████▍ | 81/150 [00:08<00:05, 13.61it/s]\n 55%|█████▌ | 83/150 [00:08<00:04, 13.61it/s]\n 57%|█████▋ | 85/150 [00:08<00:04, 13.62it/s]\n 58%|█████▊ | 87/150 [00:08<00:04, 13.67it/s]\n 59%|█████▉ | 89/150 [00:08<00:04, 13.54it/s]\n 61%|██████ | 91/150 [00:08<00:04, 13.47it/s]\n 62%|██████▏ | 93/150 [00:09<00:04, 13.56it/s]\n 63%|██████▎ | 95/150 [00:09<00:04, 13.48it/s]\n 65%|██████▍ | 97/150 [00:09<00:03, 13.48it/s]\n 66%|██████▌ | 99/150 [00:09<00:03, 13.60it/s]\n 67%|██████▋ | 101/150 [00:09<00:03, 13.63it/s]\n 69%|██████▊ | 103/150 [00:09<00:03, 13.64it/s]\n 70%|███████ | 105/150 [00:09<00:03, 13.56it/s]\n 71%|███████▏ | 107/150 [00:10<00:03, 13.57it/s]\n 73%|███████▎ | 109/150 [00:10<00:03, 13.55it/s]\n 74%|███████▍ | 111/150 [00:10<00:02, 13.64it/s]\n 75%|███████▌ | 113/150 [00:10<00:02, 13.70it/s]\n 77%|███████▋ | 115/150 [00:10<00:02, 13.57it/s]\n 78%|███████▊ | 117/150 [00:10<00:02, 13.72it/s]\n 79%|███████▉ | 119/150 [00:10<00:02, 13.82it/s]\n 81%|████████ | 121/150 [00:11<00:02, 13.86it/s]\n 82%|████████▏ | 123/150 [00:11<00:01, 13.88it/s]\n 83%|████████▎ | 125/150 [00:11<00:01, 13.90it/s]\n 85%|████████▍ | 127/150 [00:11<00:01, 13.93it/s]\n 86%|████████▌ | 129/150 [00:11<00:01, 13.80it/s]\n 87%|████████▋ | 131/150 [00:11<00:01, 13.78it/s]\n 89%|████████▊ | 133/150 [00:11<00:01, 13.80it/s]\n 90%|█████████ | 135/150 [00:12<00:01, 13.86it/s]\n 91%|█████████▏| 137/150 [00:12<00:00, 13.88it/s]\n 93%|█████████▎| 139/150 [00:12<00:00, 13.87it/s]\n 94%|█████████▍| 141/150 [00:12<00:00, 13.87it/s]\n 95%|█████████▌| 143/150 [00:12<00:00, 13.61it/s]\n 97%|█████████▋| 145/150 [00:12<00:00, 13.68it/s]\n 98%|█████████▊| 147/150 [00:13<00:00, 13.50it/s]\n 99%|█████████▉| 149/150 [00:13<00:00, 13.62it/s]\n100%|██████████| 150/150 [00:13<00:00, 11.34it/s]",
"metrics": {
"predict_time": 16.478773,
"total_time": 163.219286
},
"output": [
"https://replicate.delivery/pbxt/x1CKfwEm3OUBda2BRorIZRwaQNMrRNkIFO1uqhX5FXUdT7ePA/out-0.png"
],
"started_at": "2022-11-08T01:58:01.797339Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/2ggapwprc5cmrpxijznihpzrw4",
"cancel": "https://api.replicate.com/v1/predictions/2ggapwprc5cmrpxijznihpzrw4/cancel"
},
"version": "1f4cdaee82b13c1f92706a211f55d92d7ee87b13e2c2ba6b998a7817ffc5017f"
}Generated in
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100%|██████████| 150/150 [00:13<00:00, 11.34it/s]This example was created by a different version, tstramer/arcane-diffusion:1f4cdaee.