typetext
{
"aspect_ratio": "1:1",
"extra_lora_scale": 1,
"go_fast": true,
"guidance_scale": 3,
"height": 1024,
"lora_scale": 1,
"megapixels": "1",
"model": "dev",
"num_inference_steps": 28,
"num_outputs": 1,
"output_format": "png",
"output_quality": 80,
"prompt": "A tram model tatra t3 TATRAT3 on a city street. The tram is green and white. The tram is visible from the back side",
"prompt_strength": 0.8,
"width": 1024
}npm install replicate
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_IqH**********************************
This is your API token. Keep it to yourself.
import Replicate from "replicate";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run rinatkurmaev/flux-dev-lora-tatra-t3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"rinatkurmaev/flux-dev-lora-tatra-t3:25b2bc71bd11c42a9e7ce2f91995ded93cc12f1f23d2cbb7fff77f3da1bb65c4",
{
input: {
aspect_ratio: "1:1",
extra_lora_scale: 1,
go_fast: true,
guidance_scale: 3,
height: 1024,
lora_scale: 1,
megapixels: "1",
model: "dev",
num_inference_steps: 28,
num_outputs: 1,
output_format: "png",
output_quality: 80,
prompt: "A tram model tatra t3 TATRAT3 on a city street. The tram is green and white. The tram is visible from the back side",
prompt_strength: 0.8,
width: 1024
}
}
);
// 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=r8_IqH**********************************
This is your API token. Keep it to yourself.
import replicate
Run rinatkurmaev/flux-dev-lora-tatra-t3 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"rinatkurmaev/flux-dev-lora-tatra-t3:25b2bc71bd11c42a9e7ce2f91995ded93cc12f1f23d2cbb7fff77f3da1bb65c4",
input={
"aspect_ratio": "1:1",
"extra_lora_scale": 1,
"go_fast": True,
"guidance_scale": 3,
"height": 1024,
"lora_scale": 1,
"megapixels": "1",
"model": "dev",
"num_inference_steps": 28,
"num_outputs": 1,
"output_format": "png",
"output_quality": 80,
"prompt": "A tram model tatra t3 TATRAT3 on a city street. The tram is green and white. The tram is visible from the back side",
"prompt_strength": 0.8,
"width": 1024
}
)
# 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.
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_IqH**********************************
This is your API token. Keep it to yourself.
Run rinatkurmaev/flux-dev-lora-tatra-t3 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": "rinatkurmaev/flux-dev-lora-tatra-t3:25b2bc71bd11c42a9e7ce2f91995ded93cc12f1f23d2cbb7fff77f3da1bb65c4",
"input": {
"aspect_ratio": "1:1",
"extra_lora_scale": 1,
"go_fast": true,
"guidance_scale": 3,
"height": 1024,
"lora_scale": 1,
"megapixels": "1",
"model": "dev",
"num_inference_steps": 28,
"num_outputs": 1,
"output_format": "png",
"output_quality": 80,
"prompt": "A tram model tatra t3 TATRAT3 on a city street. The tram is green and white. The tram is visible from the back side",
"prompt_strength": 0.8,
"width": 1024
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
{
"id": "1v18fzt7j5rm80cmwaqt3w6h7m",
"model": "rinatkurmaev/flux-dev-lora-tatra-t3",
"version": "25b2bc71bd11c42a9e7ce2f91995ded93cc12f1f23d2cbb7fff77f3da1bb65c4",
"input": {
"aspect_ratio": "1:1",
"extra_lora_scale": 1,
"go_fast": true,
"guidance_scale": 3,
"height": 1024,
"lora_scale": 1,
"megapixels": "1",
"model": "dev",
"num_inference_steps": 28,
"num_outputs": 1,
"output_format": "png",
"output_quality": 80,
"prompt": "A tram model tatra t3 TATRAT3 on a city street. The tram is green and white. The tram is visible from the back side",
"prompt_strength": 0.8,
"width": 1024
},
"logs": "Lora https://replicate.delivery/xezq/5wg4NzY5IOIuMZ4bhf8BTSUhf8hq4vj2AWECTkhWETqANDNUA/trained_model.tar already loaded\nrunning quantized prediction\nUsing seed: 3788670906\n 0%| | 0/28 [00:00<?, ?it/s]\n 7%|▋ | 2/28 [00:00<00:01, 18.16it/s]\n 14%|█▍ | 4/28 [00:00<00:01, 13.10it/s]\n 21%|██▏ | 6/28 [00:00<00:01, 12.02it/s]\n 29%|██▊ | 8/28 [00:00<00:01, 11.58it/s]\n 36%|███▌ | 10/28 [00:00<00:01, 11.34it/s]\n 43%|████▎ | 12/28 [00:01<00:01, 10.95it/s]\n 50%|█████ | 14/28 [00:01<00:01, 10.92it/s]\n 57%|█████▋ | 16/28 [00:01<00:01, 10.90it/s]\n 64%|██████▍ | 18/28 [00:01<00:00, 10.89it/s]\n 71%|███████▏ | 20/28 [00:01<00:00, 10.89it/s]\n 79%|███████▊ | 22/28 [00:01<00:00, 10.79it/s]\n 86%|████████▌ | 24/28 [00:02<00:00, 10.76it/s]\n 93%|█████████▎| 26/28 [00:02<00:00, 10.80it/s]\n100%|██████████| 28/28 [00:02<00:00, 10.83it/s]\n100%|██████████| 28/28 [00:02<00:00, 11.13it/s]\nTotal safe images: 1 out of 1",
"output": [
"https://replicate.delivery/xezq/LFIFuJIrNmbyFpTfjLbF0kuIzzUlkV2QrQHdYisfkNNIVENUA/out-0.png"
],
"data_removed": false,
"error": null,
"source": "web",
"status": "succeeded",
"created_at": "2025-02-07T23:12:05.521Z",
"started_at": "2025-02-07T23:12:05.528479Z",
"completed_at": "2025-02-07T23:12:08.538917Z",
"urls": {
"cancel": "https://api.replicate.com/v1/predictions/1v18fzt7j5rm80cmwaqt3w6h7m/cancel",
"get": "https://api.replicate.com/v1/predictions/1v18fzt7j5rm80cmwaqt3w6h7m",
"stream": "https://stream.replicate.com/v1/files/bcwr-i67r3s7wkp3deztsbv3v5f4anllc6pxpuacp6rzqoawccyn3z4xq",
"web": "https://replicate.com/p/1v18fzt7j5rm80cmwaqt3w6h7m"
},
"metrics": {
"predict_time": 3.010437662,
"total_time": 3.017917
}
}