typetext
ID
nt3fj6t831rme0cmd8gr0m5w0c
Status
Succeeded
Source
Web
Hardware
H100
Total duration
Created
Webhook
–
Input
- prompt
- AISIGNATURE handwritten signature saying 'Sikai Xiao', black stylish calligraphy on white background. The person is a data analyst
- aspect_ratio
- 1:1default1:1typeenumvalue 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
- 4default1typenumeric-rangevalue typeintegerminimum1maximum4
- num_inference_steps
- 28default28typenumeric-rangevalue typeintegerminimum1maximum50
- guidance_scale
- 3default3typenumeric-rangevalue typenumbermaximum10
- output_format
- jpgdefaultwebptypeenumvalue typestringoptionswebp, jpg, png
- output_quality
- 100default80typenumeric-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": "1:1",
"extra_lora_scale": 1,
"go_fast": false,
"guidance_scale": 3,
"lora_scale": 1,
"megapixels": "1",
"model": "dev",
"num_inference_steps": 28,
"num_outputs": 4,
"output_format": "jpg",
"output_quality": 100,
"prompt": "AISIGNATURE handwritten signature saying 'Sikai Xiao', black stylish calligraphy on white background. The person is a data analyst",
"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_63p**********************************
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 gan-tu/flux-dev-ai-signature using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"gan-tu/flux-dev-ai-signature:470cdfd26449467644e2c662d7b6a661e8bb51b491152d4e992468642b618d24",
{
input: {
aspect_ratio: "1:1",
extra_lora_scale: 1,
go_fast: false,
guidance_scale: 3,
lora_scale: 1,
megapixels: "1",
model: "dev",
num_inference_steps: 28,
num_outputs: 4,
output_format: "jpg",
output_quality: 100,
prompt: "AISIGNATURE handwritten signature saying 'Sikai Xiao', black stylish calligraphy on white background. The person is a data analyst",
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_63p**********************************
This is your API token. Keep it to yourself.
Import the client:
import replicate
Run gan-tu/flux-dev-ai-signature using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"gan-tu/flux-dev-ai-signature:470cdfd26449467644e2c662d7b6a661e8bb51b491152d4e992468642b618d24",
input={
"aspect_ratio": "1:1",
"extra_lora_scale": 1,
"go_fast": False,
"guidance_scale": 3,
"lora_scale": 1,
"megapixels": "1",
"model": "dev",
"num_inference_steps": 28,
"num_outputs": 4,
"output_format": "jpg",
"output_quality": 100,
"prompt": "AISIGNATURE handwritten signature saying 'Sikai Xiao', black stylish calligraphy on white background. The person is a data analyst",
"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_63p**********************************
This is your API token. Keep it to yourself.
Run gan-tu/flux-dev-ai-signature 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": "gan-tu/flux-dev-ai-signature:470cdfd26449467644e2c662d7b6a661e8bb51b491152d4e992468642b618d24",
"input": {
"aspect_ratio": "1:1",
"extra_lora_scale": 1,
"go_fast": false,
"guidance_scale": 3,
"lora_scale": 1,
"megapixels": "1",
"model": "dev",
"num_inference_steps": 28,
"num_outputs": 4,
"output_format": "jpg",
"output_quality": 100,
"prompt": "AISIGNATURE handwritten signature saying \'Sikai Xiao\', black stylish calligraphy on white background. The person is a data analyst",
"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": "nt3fj6t831rme0cmd8gr0m5w0c",
"model": "gan-tu/flux-dev-ai-signature",
"version": "470cdfd26449467644e2c662d7b6a661e8bb51b491152d4e992468642b618d24",
"input": {
"aspect_ratio": "1:1",
"extra_lora_scale": 1,
"go_fast": false,
"guidance_scale": 3,
"lora_scale": 1,
"megapixels": "1",
"model": "dev",
"num_inference_steps": 28,
"num_outputs": 4,
"output_format": "jpg",
"output_quality": 100,
"prompt": "AISIGNATURE handwritten signature saying 'Sikai Xiao', black stylish calligraphy on white background. The person is a data analyst",
"prompt_strength": 0.8
},
"logs": "2025-01-15 13:22:33.633 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-15 13:22:33.633 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 94%|█████████▍| 285/304 [00:00<00:00, 2844.52it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2780.44it/s]\n2025-01-15 13:22:33.743 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s\nfree=29123160272896\nDownloading weights\n2025-01-15T13:22:33Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpfga5rrnb/weights url=https://replicate.delivery/xezq/g3YWaxjrj3btJ5yURCqehXOuyXqqlhvPdSu8uy5s5UWCaoCKA/trained_model.tar\n2025-01-15T13:22:34Z | INFO | [ Complete ] dest=/tmp/tmpfga5rrnb/weights size=\"172 MB\" total_elapsed=1.149s url=https://replicate.delivery/xezq/g3YWaxjrj3btJ5yURCqehXOuyXqqlhvPdSu8uy5s5UWCaoCKA/trained_model.tar\nDownloaded weights in 1.17s\n2025-01-15 13:22:34.914 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/5a7feadc97500dcd\n2025-01-15 13:22:34.984 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2025-01-15 13:22:34.984 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2025-01-15 13:22:34.984 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 94%|█████████▍| 285/304 [00:00<00:00, 2848.71it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2783.71it/s]\n2025-01-15 13:22:35.094 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.18s\nUsing seed: 62223\n0it [00:00, ?it/s]\n1it [00:00, 8.42it/s]\n2it [00:00, 5.91it/s]\n3it [00:00, 5.39it/s]\n4it [00:00, 5.17it/s]\n5it [00:00, 5.05it/s]\n6it [00:01, 4.95it/s]\n7it [00:01, 4.92it/s]\n8it [00:01, 4.90it/s]\n9it [00:01, 4.90it/s]\n10it [00:01, 4.88it/s]\n11it [00:02, 4.86it/s]\n12it [00:02, 4.86it/s]\n13it [00:02, 4.85it/s]\n14it [00:02, 4.85it/s]\n15it [00:03, 4.85it/s]\n16it [00:03, 4.85it/s]\n17it [00:03, 4.84it/s]\n18it [00:03, 4.84it/s]\n19it [00:03, 4.85it/s]\n20it [00:04, 4.85it/s]\n21it [00:04, 4.85it/s]\n22it [00:04, 4.85it/s]\n23it [00:04, 4.85it/s]\n24it [00:04, 4.85it/s]\n25it [00:05, 4.86it/s]\n26it [00:05, 4.86it/s]\n27it [00:05, 4.86it/s]\n28it [00:05, 4.85it/s]\n28it [00:05, 4.92it/s]\n0it [00:00, ?it/s]\n1it [00:00, 4.89it/s]\n2it [00:00, 4.87it/s]\n3it [00:00, 4.85it/s]\n4it [00:00, 4.85it/s]\n5it [00:01, 4.84it/s]\n6it [00:01, 4.84it/s]\n7it [00:01, 4.84it/s]\n8it [00:01, 4.84it/s]\n9it [00:01, 4.84it/s]\n10it [00:02, 4.84it/s]\n11it [00:02, 4.83it/s]\n12it [00:02, 4.84it/s]\n13it [00:02, 4.84it/s]\n14it [00:02, 4.84it/s]\n15it [00:03, 4.84it/s]\n16it [00:03, 4.84it/s]\n17it [00:03, 4.84it/s]\n18it [00:03, 4.84it/s]\n19it [00:03, 4.84it/s]\n20it [00:04, 4.84it/s]\n21it [00:04, 4.84it/s]\n22it [00:04, 4.84it/s]\n23it [00:04, 4.84it/s]\n24it [00:04, 4.84it/s]\n25it [00:05, 4.84it/s]\n26it [00:05, 4.84it/s]\n27it [00:05, 4.84it/s]\n28it [00:05, 4.85it/s]\n28it [00:05, 4.84it/s]\n0it [00:00, ?it/s]\n1it [00:00, 4.87it/s]\n2it [00:00, 4.85it/s]\n3it [00:00, 4.85it/s]\n4it [00:00, 4.83it/s]\n5it [00:01, 4.84it/s]\n6it [00:01, 4.84it/s]\n7it [00:01, 4.84it/s]\n8it [00:01, 4.83it/s]\n9it [00:01, 4.84it/s]\n10it [00:02, 4.84it/s]\n11it [00:02, 4.84it/s]\n12it [00:02, 4.84it/s]\n13it [00:02, 4.84it/s]\n14it [00:02, 4.84it/s]\n15it [00:03, 4.84it/s]\n16it [00:03, 4.84it/s]\n17it [00:03, 4.84it/s]\n18it [00:03, 4.83it/s]\n19it [00:03, 4.82it/s]\n20it [00:04, 4.83it/s]\n21it [00:04, 4.83it/s]\n22it [00:04, 4.83it/s]\n23it [00:04, 4.84it/s]\n24it [00:04, 4.84it/s]\n25it [00:05, 4.84it/s]\n26it [00:05, 4.84it/s]\n27it [00:05, 4.84it/s]\n28it [00:05, 4.84it/s]\n28it [00:05, 4.84it/s]\n0it [00:00, ?it/s]\n1it [00:00, 4.87it/s]\n2it [00:00, 4.84it/s]\n3it [00:00, 4.84it/s]\n4it [00:00, 4.82it/s]\n5it [00:01, 4.82it/s]\n6it [00:01, 4.82it/s]\n7it [00:01, 4.82it/s]\n8it [00:01, 4.82it/s]\n9it [00:01, 4.82it/s]\n10it [00:02, 4.82it/s]\n11it [00:02, 4.82it/s]\n12it [00:02, 4.82it/s]\n13it [00:02, 4.83it/s]\n14it [00:02, 4.83it/s]\n15it [00:03, 4.83it/s]\n16it [00:03, 4.82it/s]\n17it [00:03, 4.82it/s]\n18it [00:03, 4.82it/s]\n19it [00:03, 4.83it/s]\n20it [00:04, 4.83it/s]\n21it [00:04, 4.83it/s]\n22it [00:04, 4.83it/s]\n23it [00:04, 4.83it/s]\n24it [00:04, 4.84it/s]\n25it [00:05, 4.84it/s]\n26it [00:05, 4.84it/s]\n27it [00:05, 4.84it/s]\n28it [00:05, 4.84it/s]\n28it [00:05, 4.83it/s]\nTotal safe images: 4 out of 4",
"output": [
"https://replicate.delivery/xezq/jBi6hJUmQDajIhr9WLNHZ6rL3QeETf2i8TiDPx31zn1yiWFUA/out-0.jpg",
"https://replicate.delivery/xezq/WMcudQRxfmQ1Bq3XBfstScGLjCyiRlJayzB4oJ4Eo1myiWFUA/out-1.jpg",
"https://replicate.delivery/xezq/vz2d1IIroMoKKN8at3Jb3wd5SqluTC6CYW1oTI4wQRmsoVBF/out-2.jpg",
"https://replicate.delivery/xezq/hal9ybgtMiomHFSO586e7KrlxF3fEg2XTUWQynpMs97yiWFUA/out-3.jpg"
],
"data_removed": false,
"error": null,
"source": "web",
"status": "succeeded",
"created_at": "2025-01-15T13:22:33.624Z",
"started_at": "2025-01-15T13:22:33.634023Z",
"completed_at": "2025-01-15T13:22:58.745592Z",
"urls": {
"cancel": "https://api.replicate.com/v1/predictions/nt3fj6t831rme0cmd8gr0m5w0c/cancel",
"get": "https://api.replicate.com/v1/predictions/nt3fj6t831rme0cmd8gr0m5w0c",
"stream": "https://stream.replicate.com/v1/files/bcwr-moe4grsk2cerqsn7f7vpdeojrlbwo7oaxep4bfm2ix2rotceqq7a",
"web": "https://replicate.com/p/nt3fj6t831rme0cmd8gr0m5w0c"
},
"metrics": {
"predict_time": 25.111568723,
"total_time": 25.121592
}
}Generated in
2025-01-15 13:22:33.633 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2025-01-15 13:22:33.633 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s]
Applying LoRA: 94%|█████████▍| 285/304 [00:00<00:00, 2844.52it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2780.44it/s]
2025-01-15 13:22:33.743 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s
free=29123160272896
Downloading weights
2025-01-15T13:22:33Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmpfga5rrnb/weights url=https://replicate.delivery/xezq/g3YWaxjrj3btJ5yURCqehXOuyXqqlhvPdSu8uy5s5UWCaoCKA/trained_model.tar
2025-01-15T13:22:34Z | INFO | [ Complete ] dest=/tmp/tmpfga5rrnb/weights size="172 MB" total_elapsed=1.149s url=https://replicate.delivery/xezq/g3YWaxjrj3btJ5yURCqehXOuyXqqlhvPdSu8uy5s5UWCaoCKA/trained_model.tar
Downloaded weights in 1.17s
2025-01-15 13:22:34.914 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/5a7feadc97500dcd
2025-01-15 13:22:34.984 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded
2025-01-15 13:22:34.984 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys
2025-01-15 13:22:34.984 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted
Applying LoRA: 0%| | 0/304 [00:00<?, ?it/s]
Applying LoRA: 94%|█████████▍| 285/304 [00:00<00:00, 2848.71it/s]
Applying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2783.71it/s]
2025-01-15 13:22:35.094 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.18s
Using seed: 62223
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1it [00:00, 8.42it/s]
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28it [00:05, 4.84it/s]
28it [00:05, 4.83it/s]
Total safe images: 4 out of 4