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ludocomito /flux-kuji:5001e4db
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=ludocomito/flux-kuji
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 ludocomito/flux-kuji using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"ludocomito/flux-kuji:5001e4db8ed2bce55e46f4323c8735bf571a66223a2be97d082c029852b2e036",
{
input: {
model: "dev",
prompt: "sunny beach in the style of KUJI",
go_fast: false,
lora_scale: 1,
megapixels: "1",
num_outputs: 1,
aspect_ratio: "1:1",
output_format: "webp",
guidance_scale: 3.5,
output_quality: 80,
prompt_strength: 0.8,
extra_lora_scale: 0.8,
num_inference_steps: 42
}
}
);
// 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 ludocomito/flux-kuji using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"ludocomito/flux-kuji:5001e4db8ed2bce55e46f4323c8735bf571a66223a2be97d082c029852b2e036",
input={
"model": "dev",
"prompt": "sunny beach in the style of KUJI",
"go_fast": False,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3.5,
"output_quality": 80,
"prompt_strength": 0.8,
"extra_lora_scale": 0.8,
"num_inference_steps": 42
}
)
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 ludocomito/flux-kuji 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": "ludocomito/flux-kuji:5001e4db8ed2bce55e46f4323c8735bf571a66223a2be97d082c029852b2e036",
"input": {
"model": "dev",
"prompt": "sunny beach in the style of KUJI",
"go_fast": false,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3.5,
"output_quality": 80,
"prompt_strength": 0.8,
"extra_lora_scale": 0.8,
"num_inference_steps": 42
}
}' \
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": "2024-08-26T20:21:15.085923Z",
"created_at": "2024-08-26T20:20:47.944000Z",
"data_removed": false,
"error": null,
"id": "qyvp8dh8s1rm00chj1cszat6hc",
"input": {
"model": "dev",
"prompt": "sunny beach in the style of KUJI",
"lora_scale": 1,
"num_outputs": 1,
"aspect_ratio": "1:1",
"output_format": "webp",
"guidance_scale": 3.5,
"output_quality": 80,
"extra_lora_scale": 0.8,
"num_inference_steps": 42
},
"logs": "Using seed: 9545\nPrompt: sunny beach in the style of KUJI\ntxt2img mode\nUsing dev model\nfree=9530279374848\nDownloading weights\n2024-08-26T20:20:49Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpdjcmfqfx/weights url=https://replicate.delivery/yhqm/kT1XobqVJKblIl6YnYiTHMf6zti7TepRVf0KG1GbLk23pStmA/trained_model.tar\n2024-08-26T20:20:53Z | INFO | [ Complete ] dest=/tmp/tmpdjcmfqfx/weights size=\"172 MB\" total_elapsed=3.468s url=https://replicate.delivery/yhqm/kT1XobqVJKblIl6YnYiTHMf6zti7TepRVf0KG1GbLk23pStmA/trained_model.tar\nDownloaded weights in 3.50s\nLoaded LoRAs in 13.42s\n 0%| | 0/42 [00:00<?, ?it/s]\n 2%|▏ | 1/42 [00:00<00:11, 3.70it/s]\n 5%|▍ | 2/42 [00:00<00:09, 4.25it/s]\n 7%|▋ | 3/42 [00:00<00:09, 3.97it/s]\n 10%|▉ | 4/42 [00:01<00:09, 3.85it/s]\n 12%|█▏ | 5/42 [00:01<00:09, 3.79it/s]\n 14%|█▍ | 6/42 [00:01<00:09, 3.76it/s]\n 17%|█▋ | 7/42 [00:01<00:09, 3.73it/s]\n 19%|█▉ | 8/42 [00:02<00:09, 3.72it/s]\n 21%|██▏ | 9/42 [00:02<00:08, 3.71it/s]\n 24%|██▍ | 10/42 [00:02<00:08, 3.70it/s]\n 26%|██▌ | 11/42 [00:02<00:08, 3.69it/s]\n 29%|██▊ | 12/42 [00:03<00:08, 3.69it/s]\n 31%|███ | 13/42 [00:03<00:07, 3.69it/s]\n 33%|███▎ | 14/42 [00:03<00:07, 3.69it/s]\n 36%|███▌ | 15/42 [00:04<00:07, 3.69it/s]\n 38%|███▊ | 16/42 [00:04<00:07, 3.69it/s]\n 40%|████ | 17/42 [00:04<00:06, 3.69it/s]\n 43%|████▎ | 18/42 [00:04<00:06, 3.69it/s]\n 45%|████▌ | 19/42 [00:05<00:06, 3.68it/s]\n 48%|████▊ | 20/42 [00:05<00:05, 3.68it/s]\n 50%|█████ | 21/42 [00:05<00:05, 3.68it/s]\n 52%|█████▏ | 22/42 [00:05<00:05, 3.68it/s]\n 55%|█████▍ | 23/42 [00:06<00:05, 3.68it/s]\n 57%|█████▋ | 24/42 [00:06<00:04, 3.68it/s]\n 60%|█████▉ | 25/42 [00:06<00:04, 3.69it/s]\n 62%|██████▏ | 26/42 [00:06<00:04, 3.69it/s]\n 64%|██████▍ | 27/42 [00:07<00:04, 3.68it/s]\n 67%|██████▋ | 28/42 [00:07<00:03, 3.68it/s]\n 69%|██████▉ | 29/42 [00:07<00:03, 3.69it/s]\n 71%|███████▏ | 30/42 [00:08<00:03, 3.68it/s]\n 74%|███████▍ | 31/42 [00:08<00:02, 3.68it/s]\n 76%|███████▌ | 32/42 [00:08<00:02, 3.68it/s]\n 79%|███████▊ | 33/42 [00:08<00:02, 3.69it/s]\n 81%|████████ | 34/42 [00:09<00:02, 3.69it/s]\n 83%|████████▎ | 35/42 [00:09<00:01, 3.68it/s]\n 86%|████████▌ | 36/42 [00:09<00:01, 3.68it/s]\n 88%|████████▊ | 37/42 [00:09<00:01, 3.69it/s]\n 90%|█████████ | 38/42 [00:10<00:01, 3.69it/s]\n 93%|█████████▎| 39/42 [00:10<00:00, 3.68it/s]\n 95%|█████████▌| 40/42 [00:10<00:00, 3.68it/s]\n 98%|█████████▊| 41/42 [00:11<00:00, 3.68it/s]\n100%|██████████| 42/42 [00:11<00:00, 3.68it/s]\n100%|██████████| 42/42 [00:11<00:00, 3.70it/s]",
"metrics": {
"predict_time": 25.329081845,
"total_time": 27.141923
},
"output": [
"https://replicate.delivery/yhqm/iMbpFxwoKXptIhqWGGVNmKQwuSmHMyu7YKXzly5GNYsuVq1E/out-0.webp"
],
"started_at": "2024-08-26T20:20:49.756841Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/qyvp8dh8s1rm00chj1cszat6hc",
"cancel": "https://api.replicate.com/v1/predictions/qyvp8dh8s1rm00chj1cszat6hc/cancel"
},
"version": "5001e4db8ed2bce55e46f4323c8735bf571a66223a2be97d082c029852b2e036"
}Generated in
Using seed: 9545
Prompt: sunny beach in the style of KUJI
txt2img mode
Using dev model
free=9530279374848
Downloading weights
2024-08-26T20:20:49Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpdjcmfqfx/weights url=https://replicate.delivery/yhqm/kT1XobqVJKblIl6YnYiTHMf6zti7TepRVf0KG1GbLk23pStmA/trained_model.tar
2024-08-26T20:20:53Z | INFO | [ Complete ] dest=/tmp/tmpdjcmfqfx/weights size="172 MB" total_elapsed=3.468s url=https://replicate.delivery/yhqm/kT1XobqVJKblIl6YnYiTHMf6zti7TepRVf0KG1GbLk23pStmA/trained_model.tar
Downloaded weights in 3.50s
Loaded LoRAs in 13.42s
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