typetext
ID
y2hq87vapxrm80cq1nnvkbey9w
Status
Succeeded
Source
Web
Hardware
H100
Total duration
Created
Webhook
–
Input
- prompt
- VKNG
- aspect_ratio
- 16:9default1:1typeenumvalue typestringoptions1:1, 16:9, 21:9, 3:2, 2:3, 4:5, 5:4, 3:4, 4:3, 9:16, 9:21, custom
- prompt_strength
- 0.8default0.8typenumeric-rangevalue typenumbermaximum1
- model
- devdefaultdevtypeenumvalue typestringoptionsdev, schnell
- num_outputs
- 2default1typenumeric-rangevalue typeintegerminimum1maximum4
- num_inference_steps
- 28default28typenumeric-rangevalue typeintegerminimum1maximum50
- guidance_scale
- 3default3typenumeric-rangevalue typenumbermaximum10
- output_format
- pngdefaultwebptypeenumvalue typestringoptionswebp, jpg, png
- output_quality
- 80default80typenumeric-rangevalue typeintegermaximum100
- go_fast
- falsetypeboolean
- megapixels
- 1default1typeenumvalue typestringoptions1, 0.25
- lora_scale
- 1default1typenumeric-rangevalue typenumberminimum-1maximum3
- extra_lora_scale
- 1default1typenumeric-rangevalue typenumberminimum-1maximum3
{
"aspect_ratio": "16:9",
"extra_lora_scale": 1,
"go_fast": false,
"guidance_scale": 3,
"lora_scale": 1,
"megapixels": "1",
"model": "dev",
"num_inference_steps": 28,
"num_outputs": 2,
"output_format": "png",
"output_quality": 80,
"prompt": "VKNG ",
"prompt_strength": 0.8
}Install Replicate’s Node.js client library:
npm install replicate
Set the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_LVg**********************************
This is your API token. Keep it to yourself.
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 gauntlet-ai/vkng-lora-test using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"gauntlet-ai/vkng-lora-test:20ffd71ff7afa0c517f312b24b95a17e4d7de0373eccf23d0b1942ed598ad7c0",
{
input: {
aspect_ratio: "16:9",
extra_lora_scale: 1,
go_fast: false,
guidance_scale: 3,
lora_scale: 1,
megapixels: "1",
model: "dev",
num_inference_steps: 28,
num_outputs: 2,
output_format: "png",
output_quality: 80,
prompt: "VKNG ",
prompt_strength: 0.8
}
}
);
// 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 replicate
Set the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_LVg**********************************
This is your API token. Keep it to yourself.
Import the client:
import replicate
Run gauntlet-ai/vkng-lora-test using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"gauntlet-ai/vkng-lora-test:20ffd71ff7afa0c517f312b24b95a17e4d7de0373eccf23d0b1942ed598ad7c0",
input={
"aspect_ratio": "16:9",
"extra_lora_scale": 1,
"go_fast": False,
"guidance_scale": 3,
"lora_scale": 1,
"megapixels": "1",
"model": "dev",
"num_inference_steps": 28,
"num_outputs": 2,
"output_format": "png",
"output_quality": 80,
"prompt": "VKNG ",
"prompt_strength": 0.8
}
)
# To access the file URL:
print(output[0].url())
#=> "http://example.com"
# To write the file to disk:
with open("my-image.png", "wb") as file:
file.write(output[0].read())
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=r8_LVg**********************************
This is your API token. Keep it to yourself.
Run gauntlet-ai/vkng-lora-test 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": "gauntlet-ai/vkng-lora-test:20ffd71ff7afa0c517f312b24b95a17e4d7de0373eccf23d0b1942ed598ad7c0",
"input": {
"aspect_ratio": "16:9",
"extra_lora_scale": 1,
"go_fast": false,
"guidance_scale": 3,
"lora_scale": 1,
"megapixels": "1",
"model": "dev",
"num_inference_steps": 28,
"num_outputs": 2,
"output_format": "png",
"output_quality": 80,
"prompt": "VKNG ",
"prompt_strength": 0.8
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{
"id": "y2hq87vapxrm80cq1nnvkbey9w",
"model": "gauntlet-ai/vkng-lora-test",
"version": "20ffd71ff7afa0c517f312b24b95a17e4d7de0373eccf23d0b1942ed598ad7c0",
"input": {
"aspect_ratio": "16:9",
"extra_lora_scale": 1,
"go_fast": false,
"guidance_scale": 3,
"lora_scale": 1,
"megapixels": "1",
"model": "dev",
"num_inference_steps": 28,
"num_outputs": 2,
"output_format": "png",
"output_quality": 80,
"prompt": "VKNG ",
"prompt_strength": 0.8
},
"logs": "Weights already loaded\nLoaded LoRAs in 0.02s\nUsing seed: 17646\nPrompt: VKNG\n[!] txt2img mode\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:13, 2.03it/s]\n 7%|▋ | 2/28 [00:00<00:11, 2.30it/s]\n 11%|█ | 3/28 [00:01<00:11, 2.16it/s]\n 14%|█▍ | 4/28 [00:01<00:11, 2.10it/s]\n 18%|█▊ | 5/28 [00:02<00:11, 2.07it/s]\n 21%|██▏ | 6/28 [00:02<00:10, 2.05it/s]\n 25%|██▌ | 7/28 [00:03<00:10, 2.04it/s]\n 29%|██▊ | 8/28 [00:03<00:09, 2.03it/s]\n 32%|███▏ | 9/28 [00:04<00:09, 2.03it/s]\n 36%|███▌ | 10/28 [00:04<00:08, 2.02it/s]\n 39%|███▉ | 11/28 [00:05<00:08, 2.02it/s]\n 43%|████▎ | 12/28 [00:05<00:07, 2.02it/s]\n 46%|████▋ | 13/28 [00:06<00:07, 2.02it/s]\n 50%|█████ | 14/28 [00:06<00:06, 2.02it/s]\n 54%|█████▎ | 15/28 [00:07<00:06, 2.02it/s]\n 57%|█████▋ | 16/28 [00:07<00:05, 2.02it/s]\n 61%|██████ | 17/28 [00:08<00:05, 2.01it/s]\n 64%|██████▍ | 18/28 [00:08<00:04, 2.01it/s]\n 68%|██████▊ | 19/28 [00:09<00:04, 2.01it/s]\n 71%|███████▏ | 20/28 [00:09<00:03, 2.01it/s]\n 75%|███████▌ | 21/28 [00:10<00:03, 2.01it/s]\n 79%|███████▊ | 22/28 [00:10<00:02, 2.01it/s]\n 82%|████████▏ | 23/28 [00:11<00:02, 2.01it/s]\n 86%|████████▌ | 24/28 [00:11<00:01, 2.01it/s]\n 89%|████████▉ | 25/28 [00:12<00:01, 2.01it/s]\n 93%|█████████▎| 26/28 [00:12<00:00, 2.01it/s]\n 96%|█████████▋| 27/28 [00:13<00:00, 2.01it/s]\n100%|██████████| 28/28 [00:13<00:00, 2.01it/s]\n100%|██████████| 28/28 [00:13<00:00, 2.03it/s]\nTotal safe images: 2 out of 2",
"output": [
"https://replicate.delivery/xezq/bwElXvV5QEp2LBkxoJFYllpqetCeJM3kCmJHyO5QPklvhkwUA/out-0.png",
"https://replicate.delivery/xezq/9DSkDtvfUF3OaSVBZzDIsyFGt4i9u7oBqr0C9WB7gMw3QSYKA/out-1.png"
],
"data_removed": false,
"error": null,
"source": "web",
"status": "succeeded",
"created_at": "2025-05-26T16:27:12.951Z",
"started_at": "2025-05-26T16:27:12.966664Z",
"completed_at": "2025-05-26T16:27:27.718152Z",
"urls": {
"cancel": "https://api.replicate.com/v1/predictions/y2hq87vapxrm80cq1nnvkbey9w/cancel",
"get": "https://api.replicate.com/v1/predictions/y2hq87vapxrm80cq1nnvkbey9w",
"stream": "https://stream.replicate.com/v1/files/bcwr-vqfagnn345m6gyc62vwz2x5hsqbptiz5v2ammbtj7tszgt6hlvhq",
"web": "https://replicate.com/p/y2hq87vapxrm80cq1nnvkbey9w"
},
"metrics": {
"predict_time": 14.751487458,
"total_time": 14.767152
}
}Generated in
Weights already loaded
Loaded LoRAs in 0.02s
Using seed: 17646
Prompt: VKNG
[!] txt2img mode
0%| | 0/28 [00:00<?, ?it/s]
4%|▎ | 1/28 [00:00<00:13, 2.03it/s]
7%|▋ | 2/28 [00:00<00:11, 2.30it/s]
11%|█ | 3/28 [00:01<00:11, 2.16it/s]
14%|█▍ | 4/28 [00:01<00:11, 2.10it/s]
18%|█▊ | 5/28 [00:02<00:11, 2.07it/s]
21%|██▏ | 6/28 [00:02<00:10, 2.05it/s]
25%|██▌ | 7/28 [00:03<00:10, 2.04it/s]
29%|██▊ | 8/28 [00:03<00:09, 2.03it/s]
32%|███▏ | 9/28 [00:04<00:09, 2.03it/s]
36%|███▌ | 10/28 [00:04<00:08, 2.02it/s]
39%|███▉ | 11/28 [00:05<00:08, 2.02it/s]
43%|████▎ | 12/28 [00:05<00:07, 2.02it/s]
46%|████▋ | 13/28 [00:06<00:07, 2.02it/s]
50%|█████ | 14/28 [00:06<00:06, 2.02it/s]
54%|█████▎ | 15/28 [00:07<00:06, 2.02it/s]
57%|█████▋ | 16/28 [00:07<00:05, 2.02it/s]
61%|██████ | 17/28 [00:08<00:05, 2.01it/s]
64%|██████▍ | 18/28 [00:08<00:04, 2.01it/s]
68%|██████▊ | 19/28 [00:09<00:04, 2.01it/s]
71%|███████▏ | 20/28 [00:09<00:03, 2.01it/s]
75%|███████▌ | 21/28 [00:10<00:03, 2.01it/s]
79%|███████▊ | 22/28 [00:10<00:02, 2.01it/s]
82%|████████▏ | 23/28 [00:11<00:02, 2.01it/s]
86%|████████▌ | 24/28 [00:11<00:01, 2.01it/s]
89%|████████▉ | 25/28 [00:12<00:01, 2.01it/s]
93%|█████████▎| 26/28 [00:12<00:00, 2.01it/s]
96%|█████████▋| 27/28 [00:13<00:00, 2.01it/s]
100%|██████████| 28/28 [00:13<00:00, 2.01it/s]
100%|██████████| 28/28 [00:13<00:00, 2.03it/s]
Total safe images: 2 out of 2