bryantanjw/lora-test | Run with an API on Replicate

Input

checkpoint_model

string

Checkpoint Model

Default: "darkSushi25D25D_v40.safetensors"

input_prompt

string

Shift + Return to add a new line

beautiful scenery nature glass bottle landscape, purple galaxy bottlebeautiful scenery nature glass bottle landscape, purple galaxy bottle

Prompt

Default: "beautiful scenery nature glass bottle landscape, purple galaxy bottle"

negative_prompt

string

Shift + Return to add a new line

Negative Prompt

Default: "text, watermark, ugly, blurry"

steps

integer

Steps

Default: 30

seed

integer

Sampling seed, leave Empty for Random

lora

string

LoRA Model

Default: "Diana Firecracker.safetensors"

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

npx create-replicate --model=bryantanjw/lora-test

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 bryantanjw/lora-test using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "bryantanjw/lora-test:c1952953117f95569eb7e0086424322112793a13f378a99c5277348feb97118a",
  {
    input: {
      lora: "Diana Firecracker.safetensors",
      steps: 30,
      input_prompt: "beautiful scenery nature glass bottle landscape, purple galaxy bottle",
      negative_prompt: "text, watermark, ugly, blurry",
      checkpoint_model: "darkSushi25D25D_v40.safetensors"
    }
  }
);

// 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 bryantanjw/lora-test using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "bryantanjw/lora-test:c1952953117f95569eb7e0086424322112793a13f378a99c5277348feb97118a",
    input={
        "lora": "Diana Firecracker.safetensors",
        "steps": 30,
        "input_prompt": "beautiful scenery nature glass bottle landscape, purple galaxy bottle",
        "negative_prompt": "text, watermark, ugly, blurry",
        "checkpoint_model": "darkSushi25D25D_v40.safetensors"
    }
)

# To access the file URL:
print(output.url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output.read())

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 bryantanjw/lora-test 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": "bryantanjw/lora-test:c1952953117f95569eb7e0086424322112793a13f378a99c5277348feb97118a",
    "input": {
      "lora": "Diana Firecracker.safetensors",
      "steps": 30,
      "input_prompt": "beautiful scenery nature glass bottle landscape, purple galaxy bottle",
      "negative_prompt": "text, watermark, ugly, blurry",
      "checkpoint_model": "darkSushi25D25D_v40.safetensors"
    }
  }' \
  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.

Run time and cost

This model costs approximately $0.071 to run on Replicate, or 14 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 T4 GPU hardware. Predictions typically complete within 6 minutes. The predict time for this model varies significantly based on the inputs.

Readme

This model doesn't have a readme.