lucataco/diffusers-dreambooth-lora-x2:c08fbf64 | Run with an API on Replicate

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lucataco /diffusers-dreambooth-lora-x2:c08fbf64

Playground API

Input

input_images

file

A zip file containing the images that will be used for training.

instance_prompt

string

Shift + Return to add a new line

Instance prompt to trigger the image generation

Default: "a photo of TOK dog"

resolution

integer

The resolution for input images, all the images in the train/validation dataset will be resized to this

Default: 512

max_train_steps

integer

(minimum: 100, maximum: 6000)

Total number of training steps to perform

Default: 500

rank

integer

(minimum: 4, maximum: 64)

The dimension of the LoRA

Default: 4

train_batch_size

integer

(minimum: 1, maximum: 8)

Batch size for the training dataloader

Default: 1

gradient_accumulation_steps

integer

(minimum: 1, maximum: 8)

Number of updates steps to accumulate before performing a backward/update pass

Default: 1

optimizer

string

The optimizer type to use

Default: "AdamW"

learning_rate

number

(minimum: 0.0001, maximum: 1)

Initial learning rate to use (1.0 for Prodigy)

Default: 0.0001

lr_scheduler

string

'The scheduler type to use

Default: "constant"

checkpointing_steps

integer

(minimum: 100, maximum: 6000)

Save a checkpoint of the training state every X updates

seed

integer

Seed for reproducibility

backend

string

Dynamo Backend

Default: "no"

hf_token

secret

Huggingface token (optional) with write access to upload to Hugging Face

hub_model_id

string

Shift + Return to add a new line

Huggingface model location for upload. Requires a HF token with write permissions. Ex: lucataco/flux-qsd

wandb_api_key

secret

Weights and Biases API key, if you'd like to log training progress to W&B.

Run this model in Node.js with one line of code:

npx create-replicate --model=lucataco/diffusers-dreambooth-lora-x2

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

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 lucataco/diffusers-dreambooth-lora-x2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "lucataco/diffusers-dreambooth-lora-x2:c08fbf6493af92c7df4ed131d8d98601b4919a13144d5f7cd5c7bd56d6f7eaaa",
  {
    input: {
      rank: 4,
      backend: "no",
      optimizer: "AdamW",
      resolution: 512,
      lr_scheduler: "constant",
      learning_rate: 0.0001,
      instance_prompt: "a photo of TOK dog",
      max_train_steps: 500,
      train_batch_size: 1,
      gradient_accumulation_steps: 1
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output);

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=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run lucataco/diffusers-dreambooth-lora-x2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "lucataco/diffusers-dreambooth-lora-x2:c08fbf6493af92c7df4ed131d8d98601b4919a13144d5f7cd5c7bd56d6f7eaaa",
    input={
        "rank": 4,
        "backend": "no",
        "optimizer": "AdamW",
        "resolution": 512,
        "lr_scheduler": "constant",
        "learning_rate": 0.0001,
        "instance_prompt": "a photo of TOK dog",
        "max_train_steps": 500,
        "train_batch_size": 1,
        "gradient_accumulation_steps": 1
    }
)
print(output)

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=<paste-your-token-here>

Find your API token in your account settings.

Run lucataco/diffusers-dreambooth-lora-x2 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": "lucataco/diffusers-dreambooth-lora-x2:c08fbf6493af92c7df4ed131d8d98601b4919a13144d5f7cd5c7bd56d6f7eaaa",
    "input": {
      "rank": 4,
      "backend": "no",
      "optimizer": "AdamW",
      "resolution": 512,
      "lr_scheduler": "constant",
      "learning_rate": 0.0001,
      "instance_prompt": "a photo of TOK dog",
      "max_train_steps": 500,
      "train_batch_size": 1,
      "gradient_accumulation_steps": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

No output yet! Press "Submit" to start a prediction.