typetext
{
"aspect_ratio": "1:1",
"extra_lora_scale": 1,
"go_fast": false,
"guidance_scale": 10,
"height": 1024,
"lora_scale": 1,
"megapixels": "1",
"model": "dev",
"num_inference_steps": 50,
"num_outputs": 4,
"output_format": "png",
"output_quality": 100,
"prompt": "tjk in a high-resolution, documentary photo as a 34-year-old woman with blonde, chin-length hair, sitting on the grass in a field of flowers.",
"prompt_strength": 0.8,
"width": 1024
}npm install replicate
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_1zH**********************************
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 hodeehum/flux-dev-lora-trainer4 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"hodeehum/flux-dev-lora-trainer4:aad4684a4809bd363dc7de8368ecd4b9f6361cbed7bd4cf6dd62753989554db9",
{
input: {
aspect_ratio: "1:1",
extra_lora_scale: 1,
go_fast: false,
guidance_scale: 10,
height: 1024,
lora_scale: 1,
megapixels: "1",
model: "dev",
num_inference_steps: 50,
num_outputs: 4,
output_format: "png",
output_quality: 100,
prompt: "tjk in a high-resolution, documentary photo as a 34-year-old woman with blonde, chin-length hair, sitting on the grass in a field of flowers.",
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_1zH**********************************
This is your API token. Keep it to yourself.
import replicate
Run hodeehum/flux-dev-lora-trainer4 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"hodeehum/flux-dev-lora-trainer4:aad4684a4809bd363dc7de8368ecd4b9f6361cbed7bd4cf6dd62753989554db9",
input={
"aspect_ratio": "1:1",
"extra_lora_scale": 1,
"go_fast": False,
"guidance_scale": 10,
"height": 1024,
"lora_scale": 1,
"megapixels": "1",
"model": "dev",
"num_inference_steps": 50,
"num_outputs": 4,
"output_format": "png",
"output_quality": 100,
"prompt": "tjk in a high-resolution, documentary photo as a 34-year-old woman with blonde, chin-length hair, sitting on the grass in a field of flowers.",
"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_1zH**********************************
This is your API token. Keep it to yourself.
Run hodeehum/flux-dev-lora-trainer4 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": "hodeehum/flux-dev-lora-trainer4:aad4684a4809bd363dc7de8368ecd4b9f6361cbed7bd4cf6dd62753989554db9",
"input": {
"aspect_ratio": "1:1",
"extra_lora_scale": 1,
"go_fast": false,
"guidance_scale": 10,
"height": 1024,
"lora_scale": 1,
"megapixels": "1",
"model": "dev",
"num_inference_steps": 50,
"num_outputs": 4,
"output_format": "png",
"output_quality": 100,
"prompt": "tjk in a high-resolution, documentary photo as a 34-year-old woman with blonde, chin-length hair, sitting on the grass in a field of flowers.",
"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": "9k18p0pyh5rm80cm2nfah536mr",
"model": "hodeehum/flux-dev-lora-trainer4",
"version": "aad4684a4809bd363dc7de8368ecd4b9f6361cbed7bd4cf6dd62753989554db9",
"input": {
"aspect_ratio": "1:1",
"extra_lora_scale": 1,
"go_fast": false,
"guidance_scale": 10,
"height": 1024,
"lora_scale": 1,
"megapixels": "1",
"model": "dev",
"num_inference_steps": 50,
"num_outputs": 4,
"output_format": "png",
"output_quality": 100,
"prompt": "tjk in a high-resolution, documentary photo as a 34-year-old woman with blonde, chin-length hair, sitting on the grass in a field of flowers.",
"prompt_strength": 0.8,
"width": 1024
},
"logs": "2024-12-30 02:22:07.395 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2024-12-30 02:22:07.396 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 92%|█████████▏| 281/304 [00:00<00:00, 2809.05it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2725.77it/s]\n2024-12-30 02:22:07.508 | SUCCESS | fp8.lora_loading:unload_loras:564 - LoRAs unloaded in 0.11s\nfree=29917324013568\nDownloading weights\n2024-12-30T02:22:07Z | INFO | [ Initiating ] chunk_size=150M dest=/tmp/tmp9yn5ybf8/weights url=https://replicate.delivery/xezq/8dGAsHRoxHqLAdnlX3lFxgbtGWbCbcdInekMZhHmmOhf76fnA/trained_model.tar\n2024-12-30T02:22:10Z | INFO | [ Complete ] dest=/tmp/tmp9yn5ybf8/weights size=\"1.1 GB\" total_elapsed=2.933s url=https://replicate.delivery/xezq/8dGAsHRoxHqLAdnlX3lFxgbtGWbCbcdInekMZhHmmOhf76fnA/trained_model.tar\nDownloaded weights in 2.99s\n2024-12-30 02:22:10.499 | INFO | fp8.lora_loading:convert_lora_weights:498 - Loading LoRA weights for /src/weights-cache/c18631d797443ecf\n2024-12-30 02:22:10.726 | INFO | fp8.lora_loading:convert_lora_weights:519 - LoRA weights loaded\n2024-12-30 02:22:10.726 | DEBUG | fp8.lora_loading:apply_lora_to_model:574 - Extracting keys\n2024-12-30 02:22:10.726 | DEBUG | fp8.lora_loading:apply_lora_to_model:581 - Keys extracted\nApplying LoRA: 0%| | 0/304 [00:00<?, ?it/s]\nApplying LoRA: 94%|█████████▍| 287/304 [00:00<00:00, 2868.35it/s]\nApplying LoRA: 100%|██████████| 304/304 [00:00<00:00, 2759.76it/s]\n2024-12-30 02:22:10.837 | SUCCESS | fp8.lora_loading:load_lora:539 - LoRA applied in 0.34s\nUsing seed: 2405\n0it [00:00, ?it/s]\n1it [00:00, 8.40it/s]\n2it [00:00, 5.89it/s]\n3it [00:00, 5.37it/s]\n4it [00:00, 5.15it/s]\n5it [00:00, 5.02it/s]\n6it [00:01, 4.94it/s]\n7it [00:01, 4.91it/s]\n8it [00:01, 4.89it/s]\n9it [00:01, 4.87it/s]\n10it [00:01, 4.86it/s]\n11it [00:02, 4.84it/s]\n12it [00:02, 4.83it/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, 4.82it/s]\n20it [00:04, 4.82it/s]\n21it [00:04, 4.82it/s]\n22it [00:04, 4.81it/s]\n23it [00:04, 4.82it/s]\n24it [00:04, 4.81it/s]\n25it [00:05, 4.81it/s]\n26it [00:05, 4.81it/s]\n27it [00:05, 4.81it/s]\n28it [00:05, 4.81it/s]\n29it [00:05, 4.82it/s]\n30it [00:06, 4.82it/s]\n31it [00:06, 4.82it/s]\n32it [00:06, 4.82it/s]\n33it [00:06, 4.82it/s]\n34it [00:06, 4.82it/s]\n35it [00:07, 4.82it/s]\n36it [00:07, 4.81it/s]\n37it [00:07, 4.81it/s]\n38it [00:07, 4.81it/s]\n39it [00:08, 4.82it/s]\n40it [00:08, 4.82it/s]\n41it [00:08, 4.81it/s]\n42it [00:08, 4.81it/s]\n43it [00:08, 4.81it/s]\n44it [00:09, 4.81it/s]\n45it [00:09, 4.81it/s]\n46it [00:09, 4.81it/s]\n47it [00:09, 4.81it/s]\n48it [00:09, 4.82it/s]\n49it [00:10, 4.82it/s]\n50it [00:10, 4.82it/s]\n50it [00:10, 4.86it/s]\n0it [00:00, ?it/s]\n1it [00:00, 4.82it/s]\n2it [00:00, 4.79it/s]\n3it [00:00, 4.80it/s]\n4it [00:00, 4.81it/s]\n5it [00:01, 4.81it/s]\n6it [00:01, 4.80it/s]\n7it [00:01, 4.80it/s]\n8it [00:01, 4.80it/s]\n9it [00:01, 4.81it/s]\n10it [00:02, 4.82it/s]\n11it [00:02, 4.81it/s]\n12it [00:02, 4.81it/s]\n13it [00:02, 4.81it/s]\n14it [00:02, 4.81it/s]\n15it [00:03, 4.81it/s]\n16it [00:03, 4.81it/s]\n17it [00:03, 4.81it/s]\n18it [00:03, 4.81it/s]\n19it [00:03, 4.81it/s]\n20it [00:04, 4.81it/s]\n21it [00:04, 4.81it/s]\n22it [00:04, 4.81it/s]\n23it [00:04, 4.81it/s]\n24it [00:04, 4.81it/s]\n25it [00:05, 4.81it/s]\n26it [00:05, 4.80it/s]\n27it [00:05, 4.80it/s]\n28it [00:05, 4.80it/s]\n29it [00:06, 4.81it/s]\n30it [00:06, 4.81it/s]\n31it [00:06, 4.81it/s]\n32it [00:06, 4.81it/s]\n33it [00:06, 4.81it/s]\n34it [00:07, 4.80it/s]\n35it [00:07, 4.80it/s]\n36it [00:07, 4.80it/s]\n37it [00:07, 4.81it/s]\n38it [00:07, 4.81it/s]\n39it [00:08, 4.81it/s]\n40it [00:08, 4.80it/s]\n41it [00:08, 4.80it/s]\n42it [00:08, 4.80it/s]\n43it [00:08, 4.80it/s]\n44it [00:09, 4.80it/s]\n45it [00:09, 4.81it/s]\n46it [00:09, 4.81it/s]\n47it [00:09, 4.80it/s]\n48it [00:09, 4.81it/s]\n49it [00:10, 4.81it/s]\n50it [00:10, 4.81it/s]\n50it [00:10, 4.81it/s]\n0it [00:00, ?it/s]\n1it [00:00, 4.83it/s]\n2it [00:00, 4.81it/s]\n3it [00:00, 4.82it/s]\n4it [00:00, 4.82it/s]\n5it [00:01, 4.81it/s]\n6it [00:01, 4.81it/s]\n7it [00:01, 4.81it/s]\n8it [00:01, 4.81it/s]\n9it [00:01, 4.80it/s]\n10it [00:02, 4.81it/s]\n11it [00:02, 4.81it/s]\n12it [00:02, 4.81it/s]\n13it [00:02, 4.81it/s]\n14it [00:02, 4.81it/s]\n15it [00:03, 4.81it/s]\n16it [00:03, 4.81it/s]\n17it [00:03, 4.81it/s]\n18it [00:03, 4.81it/s]\n19it [00:03, 4.80it/s]\n20it [00:04, 4.80it/s]\n21it [00:04, 4.80it/s]\n22it [00:04, 4.80it/s]\n23it [00:04, 4.81it/s]\n24it [00:04, 4.81it/s]\n25it [00:05, 4.81it/s]\n26it [00:05, 4.81it/s]\n27it [00:05, 4.81it/s]\n28it [00:05, 4.80it/s]\n29it [00:06, 4.80it/s]\n30it [00:06, 4.80it/s]\n31it [00:06, 4.80it/s]\n32it [00:06, 4.81it/s]\n33it [00:06, 4.81it/s]\n34it [00:07, 4.81it/s]\n35it [00:07, 4.80it/s]\n36it [00:07, 4.80it/s]\n37it [00:07, 4.80it/s]\n38it [00:07, 4.80it/s]\n39it [00:08, 4.80it/s]\n40it [00:08, 4.81it/s]\n41it [00:08, 4.81it/s]\n42it [00:08, 4.80it/s]\n43it [00:08, 4.81it/s]\n44it [00:09, 4.81it/s]\n45it [00:09, 4.80it/s]\n46it [00:09, 4.81it/s]\n47it [00:09, 4.81it/s]\n48it [00:09, 4.81it/s]\n49it [00:10, 4.81it/s]\n50it [00:10, 4.81it/s]\n50it [00:10, 4.81it/s]\n0it [00:00, ?it/s]\n1it [00:00, 4.84it/s]\n2it [00:00, 4.81it/s]\n3it [00:00, 4.81it/s]\n4it [00:00, 4.80it/s]\n5it [00:01, 4.78it/s]\n6it [00:01, 4.80it/s]\n7it [00:01, 4.79it/s]\n8it [00:01, 4.79it/s]\n9it [00:01, 4.79it/s]\n10it [00:02, 4.78it/s]\n11it [00:02, 4.79it/s]\n12it [00:02, 4.79it/s]\n13it [00:02, 4.80it/s]\n14it [00:02, 4.80it/s]\n15it [00:03, 4.79it/s]\n16it [00:03, 4.80it/s]\n17it [00:03, 4.80it/s]\n18it [00:03, 4.81it/s]\n19it [00:03, 4.81it/s]\n20it [00:04, 4.80it/s]\n21it [00:04, 4.79it/s]\n22it [00:04, 4.80it/s]\n23it [00:04, 4.81it/s]\n24it [00:05, 4.81it/s]\n25it [00:05, 4.80it/s]\n26it [00:05, 4.80it/s]\n27it [00:05, 4.81it/s]\n28it [00:05, 4.80it/s]\n29it [00:06, 4.80it/s]\n30it [00:06, 4.80it/s]\n31it [00:06, 4.79it/s]\n32it [00:06, 4.79it/s]\n33it [00:06, 4.80it/s]\n34it [00:07, 4.81it/s]\n35it [00:07, 4.81it/s]\n36it [00:07, 4.80it/s]\n37it [00:07, 4.80it/s]\n38it [00:07, 4.81it/s]\n39it [00:08, 4.81it/s]\n40it [00:08, 4.81it/s]\n41it [00:08, 4.79it/s]\n42it [00:08, 4.79it/s]\n43it [00:08, 4.80it/s]\n44it [00:09, 4.81it/s]\n45it [00:09, 4.81it/s]\n46it [00:09, 4.81it/s]\n47it [00:09, 4.81it/s]\n48it [00:09, 4.80it/s]\n49it [00:10, 4.80it/s]\n50it [00:10, 4.81it/s]\n50it [00:10, 4.80it/s]\nTotal safe images: 4 out of 4",
"output": [
"https://replicate.delivery/xezq/QrUZhRHAUIpODpDLiWSV5egBqsGXLskNqWMYWPyCV5GfX7fnA/out-0.png",
"https://replicate.delivery/xezq/e628aBBjfws1GUSujVG0vBRpP9Z9XmF2yGLASTKu2Poev2fPB/out-1.png",
"https://replicate.delivery/xezq/r8JXbghaoMZAKxNe5TxrrzQmESY76ISNVvAfB2Y1yxkev2fPB/out-2.png",
"https://replicate.delivery/xezq/ldfyKN05W0w6ICnBxAiWrzy7HrovPoXqdo0uFOP5jzfev2fPB/out-3.png"
],
"data_removed": false,
"error": null,
"source": "web",
"status": "succeeded",
"created_at": "2024-12-30T02:22:06.473Z",
"started_at": "2024-12-30T02:22:07.396883Z",
"completed_at": "2024-12-30T02:22:54.25416Z",
"urls": {
"cancel": "https://api.replicate.com/v1/predictions/9k18p0pyh5rm80cm2nfah536mr/cancel",
"get": "https://api.replicate.com/v1/predictions/9k18p0pyh5rm80cm2nfah536mr",
"stream": "https://stream.replicate.com/v1/files/bcwr-ez6plal2s437ricjmfvvvbr77h5neqnavrgkybq2m427yy6rvwuq",
"web": "https://replicate.com/p/9k18p0pyh5rm80cm2nfah536mr"
},
"metrics": {
"predict_time": 46.857277524,
"total_time": 47.78116
}
}


