edenartlab/sdxl-lora-trainer:d5b30976 – Run with an API on Replicate

Version

You're looking at a specific version of this model. Jump to the model overview.

edenartlab /sdxl-lora-trainer:d5b30976

Playground API

Input

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

npx create-replicate --model=edenartlab/sdxl-lora-trainer

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";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run edenartlab/sdxl-lora-trainer using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "edenartlab/sdxl-lora-trainer:d5b30976ba5b1d30fb2b6c4425002ae7ba36b079f2a53fb228df59e60b51b041",
  {
    input: {
      lora_rank: 4,
      lr_flip_p: 0.5,
      checkpoint: "sdxl-v1.0",
      resolution: 960,
      learning_rate: 0.0003,
      max_train_steps: 400,
      train_batch_size: 2,
      gradient_accumulation_steps: 2
    }
  }
);

console.log(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 edenartlab/sdxl-lora-trainer using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "edenartlab/sdxl-lora-trainer:d5b30976ba5b1d30fb2b6c4425002ae7ba36b079f2a53fb228df59e60b51b041",
    input={
        "lora_rank": 4,
        "lr_flip_p": 0.5,
        "checkpoint": "sdxl-v1.0",
        "resolution": 960,
        "learning_rate": 0.0003,
        "max_train_steps": 400,
        "train_batch_size": 2,
        "gradient_accumulation_steps": 2
    }
)

# The edenartlab/sdxl-lora-trainer model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
    # https://replicate.com/edenartlab/sdxl-lora-trainer/api#output-schema
    print(item)

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 edenartlab/sdxl-lora-trainer 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": "d5b30976ba5b1d30fb2b6c4425002ae7ba36b079f2a53fb228df59e60b51b041",
    "input": {
      "lora_rank": 4,
      "lr_flip_p": 0.5,
      "checkpoint": "sdxl-v1.0",
      "resolution": 960,
      "learning_rate": 0.0003,
      "max_train_steps": 400,
      "train_batch_size": 2,
      "gradient_accumulation_steps": 2
    }
  }' \
  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.