Readme
This model doesn't have a readme.
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 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:d4fc34988186e2f4e3ccd9d60499519f1be93bb23d616a7567c0a933150be135",
{
input: {
model: "dev",
prompt: "AISIGNATURE handwritten signature saying 'Sikai Xiao', black stylish calligraphy on white background. The person is a data analyst",
go_fast: false,
lora_scale: 1,
megapixels: "1",
num_outputs: 4,
aspect_ratio: "1:1",
output_format: "jpg",
guidance_scale: 3,
output_quality: 100,
prompt_strength: 0.8,
extra_lora_scale: 1,
num_inference_steps: 28
}
}
);
// 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 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:d4fc34988186e2f4e3ccd9d60499519f1be93bb23d616a7567c0a933150be135",
input={
"model": "dev",
"prompt": "AISIGNATURE handwritten signature saying 'Sikai Xiao', black stylish calligraphy on white background. The person is a data analyst",
"go_fast": False,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 4,
"aspect_ratio": "1:1",
"output_format": "jpg",
"guidance_scale": 3,
"output_quality": 100,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 28
}
)
# 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=<paste-your-token-here>
Find your API token in your account settings.
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:d4fc34988186e2f4e3ccd9d60499519f1be93bb23d616a7567c0a933150be135",
"input": {
"model": "dev",
"prompt": "AISIGNATURE handwritten signature saying \'Sikai Xiao\', black stylish calligraphy on white background. The person is a data analyst",
"go_fast": false,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 4,
"aspect_ratio": "1:1",
"output_format": "jpg",
"guidance_scale": 3,
"output_quality": 100,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 28
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Add a payment method to run this model.
By signing in, you agree to our
terms of service and privacy policy
{
"completed_at": "2025-01-15T13:22:58.745592Z",
"created_at": "2025-01-15T13:22:33.624000Z",
"data_removed": false,
"error": null,
"id": "nt3fj6t831rme0cmd8gr0m5w0c",
"input": {
"model": "dev",
"prompt": "AISIGNATURE handwritten signature saying 'Sikai Xiao', black stylish calligraphy on white background. The person is a data analyst",
"go_fast": false,
"lora_scale": 1,
"megapixels": "1",
"num_outputs": 4,
"aspect_ratio": "1:1",
"output_format": "jpg",
"guidance_scale": 3,
"output_quality": 100,
"prompt_strength": 0.8,
"extra_lora_scale": 1,
"num_inference_steps": 28
},
"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",
"metrics": {
"predict_time": 25.111568723,
"total_time": 25.121592
},
"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"
],
"started_at": "2025-01-15T13:22:33.634023Z",
"status": "succeeded",
"urls": {
"stream": "https://stream.replicate.com/v1/files/bcwr-moe4grsk2cerqsn7f7vpdeojrlbwo7oaxep4bfm2ix2rotceqq7a",
"get": "https://api.replicate.com/v1/predictions/nt3fj6t831rme0cmd8gr0m5w0c",
"cancel": "https://api.replicate.com/v1/predictions/nt3fj6t831rme0cmd8gr0m5w0c/cancel"
},
"version": "470cdfd26449467644e2c662d7b6a661e8bb51b491152d4e992468642b618d24"
}
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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Total safe images: 4 out of 4
This output was created using a different version of the model, gan-tu/flux-dev-ai-signature:470cdfd2.
This model costs approximately $0.013 to run on Replicate, or 76 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.
This model runs on Nvidia H100 GPU hardware. Predictions typically complete within 9 seconds.
This model doesn't have a readme.
This model is warm. You'll get a fast response if the model is warm and already running, and a slower response if the model is cold and starting up.
This model costs approximately $0.013 to run on Replicate, but this varies depending on your inputs. View more.
Choose a file from your machine
Hint: you can also drag files onto the input
Choose a file from your machine
Hint: you can also drag files onto the input
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, 4.87it/s]
2it [00:00, 4.84it/s]
3it [00:00, 4.84it/s]
4it [00:00, 4.82it/s]
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Total safe images: 4 out of 4