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Train Flux LoRAs For Portraits Training

fal-ai/flux-lora-portrait-trainer
FLUX LoRA training optimized for portrait generation, with bright highlights, excellent prompt following and highly detailed results.
Training
Commercial use
Schema
PlaygroundAPI

About

Fine Tune

1. Calling the API#

Install the client#

The client provides a convenient way to interact with the model API.

npm install --save @fal-ai/client

Setup your API Key#

Set FAL_KEY as an environment variable in your runtime.

export FAL_KEY="YOUR_API_KEY"

Submit a request#

The client API handles the API submit protocol. It will handle the request status updates and return the result when the request is completed.

import { fal } from "@fal-ai/client";

const result = await fal.subscribe("fal-ai/flux-lora-portrait-trainer", {
  input: {
    images_data_url: ""
  },
  logs: true,
  onQueueUpdate: (update) => {
    if (update.status === "IN_PROGRESS") {
      update.logs.map((log) => log.message).forEach(console.log);
    }
  },
});
console.log(result.data);
console.log(result.requestId);

2. Authentication#

The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.

API Key#

In case your app is running in an environment where you cannot set environment variables, you can set the API Key manually as a client configuration.
import { fal } from "@fal-ai/client";

fal.config({
  credentials: "YOUR_FAL_KEY"
});

3. Queue#

Submit a request#

The client API provides a convenient way to submit requests to the model.

import { fal } from "@fal-ai/client";

const { request_id } = await fal.queue.submit("fal-ai/flux-lora-portrait-trainer", {
  input: {
    images_data_url: ""
  },
  webhookUrl: "https://optional.webhook.url/for/results",
});

Fetch request status#

You can fetch the status of a request to check if it is completed or still in progress.

import { fal } from "@fal-ai/client";

const status = await fal.queue.status("fal-ai/flux-lora-portrait-trainer", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
  logs: true,
});

Get the result#

Once the request is completed, you can fetch the result. See the Output Schema for the expected result format.

import { fal } from "@fal-ai/client";

const result = await fal.queue.result("fal-ai/flux-lora-portrait-trainer", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);

4. Files#

Some attributes in the API accept file URLs as input. Whenever that's the case you can pass your own URL or a Base64 data URI.

Data URI (base64)#

You can pass a Base64 data URI as a file input. The API will handle the file decoding for you. Keep in mind that for large files, this alternative although convenient can impact the request performance.

Hosted files (URL)#

You can also pass your own URLs as long as they are publicly accessible. Be aware that some hosts might block cross-site requests, rate-limit, or consider the request as a bot.

Uploading files#

We provide a convenient file storage that allows you to upload files and use them in your requests. You can upload files using the client API and use the returned URL in your requests.

import { fal } from "@fal-ai/client";

const file = new File(["Hello, World!"], "hello.txt", { type: "text/plain" });
const url = await fal.storage.upload(file);

Read more about file handling in our file upload guide.

5. Schema#

Input#

images_data_url string* required

URL to zip archive with images of a consistent style. Try to use at least 10 images, although more is better.

In addition to images the archive can contain text files with captions. Each text file should have the same name as the image file it corresponds to.

The captions can include a special string [trigger]. If a trigger_word is specified, it will replace [trigger] in the captions.

trigger_phrase string

Trigger phrase to be used in the captions. If None, a trigger word will not be used. If no captions are provide the trigger_work will be used instead of captions. If captions are provided, the trigger word will replace the [trigger] string in the captions.

learning_rate float

Learning rate to use for training. Default value: 0.00009

steps integer

Number of steps to train the LoRA on. Default value: 2500

multiresolution_training boolean

If True, multiresolution training will be used. Default value: true

subject_crop boolean

If True, the subject will be cropped from the image. Default value: true

data_archive_format string

The format of the archive. If not specified, the format will be inferred from the URL.

resume_from_checkpoint string

URL to a checkpoint to resume training from. Default value: ""

{
  "images_data_url": "",
  "learning_rate": 0.0002,
  "steps": 1000,
  "multiresolution_training": true,
  "subject_crop": true
}

Output#

diffusers_lora_file File* required

URL to the trained diffusers lora weights.

config_file File* required

URL to the training configuration file.

{
  "diffusers_lora_file": {
    "url": "",
    "content_type": "image/png",
    "file_name": "z9RV14K95DvU.png",
    "file_size": 4404019
  },
  "config_file": {
    "url": "",
    "content_type": "image/png",
    "file_name": "z9RV14K95DvU.png",
    "file_size": 4404019
  }
}

Other types#

File#

url string* required

The URL where the file can be downloaded from.

content_type string

The mime type of the file.

file_name string

The name of the file. It will be auto-generated if not provided.

file_size integer

The size of the file in bytes.

file_data string

File data