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doriandarko /lcm-hiroshinagai:b43c25e9
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 doriandarko/lcm-hiroshinagai using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"doriandarko/lcm-hiroshinagai:b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faa",
{
input: {
seed: 1989,
width: 1024,
height: 1024,
prompt: "In the style of TOK, a car in the countryside",
scheduler: "LCM",
lora_scale: 0.6,
num_outputs: 4,
guidance_scale: 2,
apply_watermark: true,
negative_prompt: "black and white, ugly, ",
prompt_strength: 0.8,
num_inference_steps: 6
}
}
);
// 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 doriandarko/lcm-hiroshinagai using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"doriandarko/lcm-hiroshinagai:b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faa",
input={
"seed": 1989,
"width": 1024,
"height": 1024,
"prompt": "In the style of TOK, a car in the countryside",
"scheduler": "LCM",
"lora_scale": 0.6,
"num_outputs": 4,
"guidance_scale": 2,
"apply_watermark": True,
"negative_prompt": "black and white, ugly, ",
"prompt_strength": 0.8,
"num_inference_steps": 6
}
)
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 doriandarko/lcm-hiroshinagai 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": "doriandarko/lcm-hiroshinagai:b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faa",
"input": {
"seed": 1989,
"width": 1024,
"height": 1024,
"prompt": "In the style of TOK, a car in the countryside",
"scheduler": "LCM",
"lora_scale": 0.6,
"num_outputs": 4,
"guidance_scale": 2,
"apply_watermark": true,
"negative_prompt": "black and white, ugly, ",
"prompt_strength": 0.8,
"num_inference_steps": 6
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
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Output
{
"completed_at": "2023-11-15T05:19:27.124220Z",
"created_at": "2023-11-15T05:19:11.798636Z",
"data_removed": false,
"error": null,
"id": "rvfyredbs74pkb7xsyhv5dtb34",
"input": {
"seed": 1989,
"width": 1024,
"height": 1024,
"prompt": "In the style of TOK, a car in the countryside",
"scheduler": "LCM",
"lora_scale": 0.6,
"num_outputs": 4,
"guidance_scale": 2,
"apply_watermark": true,
"negative_prompt": "black and white, ugly, ",
"prompt_strength": 0.8,
"num_inference_steps": 6
},
"logs": "Using seed: 1989\nskipping loading .. weights already loaded\nPrompt: In the style of <s0><s1>, a car in the countryside\ntxt2img mode\nThe config attributes {'skip_prk_steps': True} were passed to LCMScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.\n 0%| | 0/6 [00:00<?, ?it/s]\n 17%|█▋ | 1/6 [00:00<00:04, 1.02it/s]\n 33%|███▎ | 2/6 [00:01<00:03, 1.02it/s]\n 50%|█████ | 3/6 [00:02<00:02, 1.02it/s]\n 67%|██████▋ | 4/6 [00:03<00:01, 1.01it/s]\n 83%|████████▎ | 5/6 [00:04<00:00, 1.01it/s]\n100%|██████████| 6/6 [00:05<00:00, 1.01it/s]\n100%|██████████| 6/6 [00:05<00:00, 1.01it/s]",
"metrics": {
"predict_time": 13.080076,
"total_time": 15.325584
},
"output": [
"https://replicate.delivery/pbxt/CWhnp689hh5AKZvfyxNKFJzarCFQxOfq0VpvqWewzJI52AxjA/out-0.png",
"https://replicate.delivery/pbxt/fu5oAgiiHd10bqnWA49QsvEfmux3vyDGogTaLCZH14kdbg4RA/out-1.png",
"https://replicate.delivery/pbxt/QJSZ0Dbn9pbXOt8qrDItHsfOtK9GMfzVel2kUydueZf1bDEPC/out-2.png",
"https://replicate.delivery/pbxt/UQ9dsOn0gfyJY6FkMN4gQbNz7vf7BpwhKla7KGikvJ4e2AxjA/out-3.png"
],
"started_at": "2023-11-15T05:19:14.044144Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/rvfyredbs74pkb7xsyhv5dtb34",
"cancel": "https://api.replicate.com/v1/predictions/rvfyredbs74pkb7xsyhv5dtb34/cancel"
},
"version": "b43c25e9643af233e1258c839b6c6726504cbc25a1843ff80d83d911b8c99faa"
}
Using seed: 1989
skipping loading .. weights already loaded
Prompt: In the style of <s0><s1>, a car in the countryside
txt2img mode
The config attributes {'skip_prk_steps': True} were passed to LCMScheduler, but are not expected and will be ignored. Please verify your scheduler_config.json configuration file.
0%| | 0/6 [00:00<?, ?it/s]
17%|█▋ | 1/6 [00:00<00:04, 1.02it/s]
33%|███▎ | 2/6 [00:01<00:03, 1.02it/s]
50%|█████ | 3/6 [00:02<00:02, 1.02it/s]
67%|██████▋ | 4/6 [00:03<00:01, 1.01it/s]
83%|████████▎ | 5/6 [00:04<00:00, 1.01it/s]
100%|██████████| 6/6 [00:05<00:00, 1.01it/s]
100%|██████████| 6/6 [00:05<00:00, 1.01it/s]